MCA2020 Syllabus

Savitribai Phule Pune University, Pune
Faculty of Commerce and Management

Master of Computer Applications (MCA)
Programme Curriculum ( Sem. I & II)

(2020-2022)
Preamble:
1. The name of the programme shall be Masters of Computer Applications (M.C.A)
2. The revised MCA Curriculum 2020 builds on the implementation of the Choice Based Credit System
(CBCS) and Grading System initiated in the AY 2015. The curriculum takes the MCA programme to
the next level in terms of implementing Outcome Based Education along with the Choice Based
Credit System (CBCS) and Grading System.
3. The Institutes should organize placement programme for M.C.A. students by interacting with
Industries and software consultancy.
4. At the end of each semester, appearing for various certifications is possible for each student
enabling them to make their resume rich.
5. With the rapidly changing scenario industry and academia should identify possible areas of
collaboration and work together. Institute’s placement cell should focus on identifying industrial
expectations and institutional preparation for meeting industrial needs.
Introduction:
1. Definition: Outcome Based Education:
1.1 Outcome Based Education (OBE) Approach: Outcomes are about performance, and this implies:
1.1.1 There must be a performer – the student (learner), not only the teacher
1.1.2 There must be something performable (thus demonstrable or assessable) to perform
1.1.3 The focus is on the performance, not the activity or task to be performed
1.2 Programme Educational Objectives (PEOs): Programme educational objectives are broad
statements that describe the career and professional accomplishments that the programme is
preparing graduates to achieve. Programme Educational Objectives are a set of broad future
focused learner’s performance outcomes that explicitly identify what learners will be able to do
with what they have learned, and what they will be like after they leave institution and are living
full and productive lives. Thus, PEOs are what the programme is preparing graduates for in their
career and professional life (to attain within a few years after graduation).
1.3 Programme Outcomes (POs): Programme Outcomes are a set of narrow statements that describes
what students (learners) of the programme are expected to know and be able to perform or attain
by the time of graduation.
1.4 Course Outcomes (COs): Course Outcomes are narrower statements that describe what students
are expected to know and be able to do at the end of each course. These relate to the skills,
knowledge, and behavior that students acquire in their matriculation through the course.
1.5 Learning Outcomes: A learning outcome is what a student CAN DO because of a learning
experience. It describes a specific task that he/she can perform at a given level of competence
under a certain situation. The three broad types of learning outcomes are: a) Disciplinary
knowledge and skills b) Generic skills c) Attitudes and values
1.6 Teaching and Learning Activities (TLAs): The set of pedagogical tools and techniques or the
teaching and learning activities that aim to help students to attain the intended learning outcomes
and engage them in these learning activities through the teaching process.
1.7 Assessment and Evaluation: Assessment is one or more processes, carried out by the institution,
that identify, collect, and prepare data to evaluate the achievement of programme educational
objectives and programme outcomes. Evaluation is one or more processes, done by the evaluation
team, for interpreting the data and evidence accumulated through assessment practices.
Evaluation
1.8 determines the extent to which programme educational objectives or programme outcomes are
being achieved, and results in decisions and actions to improve the programme.
2. MCA Programme Focus:
The basic objective of the Master of Computer Applications (MCA) is to provide a steady stream of
necessary knowledge, skills and foundation for acquiring a wide range of rewarding careers into rapidly
expanding world of Information Technology
2.1 Programme Educational Objectives: PEOs are defined by institution. Following are the guidelines
for defining PEOs
2.1.1 PEOs should be assessable and realistic within the context of the committed resources.
2.1.2 The PEOs should be consistent with the mission of the institution.
2.1.3 All the stakeholders should participate in the process of framing PEOs.
2.1.4 The number of PEOs should be manageable.
2.1.5 It should be based on the needs of the stakeholders.
2.1.6 It should be achievable by the programme.
2.1.7 It should be specific to the programme and not too broad.
2.1.8 It should not be too narrow and similar to the POs.
2.2 MCA Programme Outcomes (POs): At the end of the MCA programme the learner will possess the
following Program Outcome:
PO1: Apply knowledge of computing fundamentals, computing specialization, mathematics, and

domain knowledge appropriate for the computing specialization to the abstraction and
conceptualization of computing models from defined problems and requirements.
PO2: Identify, formulate, research literature, and solve complex Computing problems reaching
substantiated conclusions using fundamental principles of Mathematics, Computing sciences, and
relevant domain disciplines.
PO3: Design and evaluate solutions for complex computing problems, and design and evaluate
systems, components, or processes that meet specified needs with appropriate consideration for
public health and safety, cultural, societal, and environmental considerations.
PO4: Use research-based knowledge and research methods including design of experiments,
analysis and interpretation of data, and synthesis of information to provide valid conclusions.
PO5: Create, select, adapt and apply appropriate techniques, resources, and modern computing
tools to complex computing activities, with an understanding of the limitations.
PO6: Understand and commit to professional ethics and cyber regulations, responsibilities, and
norms of professional computing practice.
PO7: Recognize the need, and have the ability, to engage in independent learning for continual
development as a Computing professional.
PO8: Demonstrate knowledge and understanding of computing and management principles and
apply these to one’s own work, as a member and leader in a team, to manage projects and in
multidisciplinary environments.
PO9: Communicate effectively with the computing community, and with society at large, about
complex computing activities by being able to comprehend and write effective reports, design
documentation, make effective presentations, and give and understand clear instructions.
PO10: Understand and assess societal, environmental, health, safety, legal, and cultural issues
within local and global contexts, and the consequential responsibilities relevant to professional
computing practice.
PO11: Function effectively as an individual and as a member or leader in diverse teams and in
multidisciplinary environments.
PO12: Identify a timely opportunity and using innovation to pursue that opportunity to create
value and wealth for the betterment of the individual and society at large.
3. Admission Details:
3.1 Eligibility for Admission: The eligibility criteria for admission for the MCA course will be as decided
by the All Indian Council of Technical Education (AICTE), New Delhi and Directorate of Technical
Education (DTE), Government of Maharashtra. It will be published on their respective websites time to
time.
3.2 Reservation of Seat: The percentage of seat reserved for candidates belonging to backward classes
only from Maharashtra State in all the Government Aided, Un-aided Institutions/Colleges and
University Departments is as per the norms given by Government of Maharashtra, time to time.
3.3 Selection Basis: The selection would be done as per the guidelines given by the Director of
Technical Education, Maharashtra State, time to time.
4. Lecture-Practical/Project-Tutorial (L-P-T)
A course shall have either or all the three components, i.e. a course may have only lecture component,
or only practical/project component or a combination of any two/three components
4.1 Lecture(L): Classroom sessions delivered by faculty in an interactive mode. It should be conducted
as per the scheme of lectures indicated in respective course.
4.2 Practical/Project(P): Practical / Project Work consisting of Hands-on experience /Field Studies /
Case studies that equip students to acquire the much-required skill component. Besides separate
Practical/Project course, three courses in each semester include few practical assignments and it
will be evaluated under internal evaluation
4.3 Tutorial(T): Session consisting of participatory discussion/ self-study/ desk work/ brief seminar
presentations by students and such other novel methods that make a student to absorb and
assimilate more effectively the contents delivered in the Lecture sessions
4.4 A Mini project is an assignment that the student needs to complete at the end of every semester in
order to strengthen the understanding of fundamentals through effective application of the
courses learnt. The details guidelines have been given in the course structure.
4.5 The Project Work to be conducted in the FINAL Semester and evaluated at the end of the
semester. The detail guidelines have been in the respective course structure.
4.6 The teaching / learning as well as evaluation are to be interpreted in a broader perspective as
follows:
i) Teaching – Learning Processes: Classroom sessions, Group Exercises, Seminars, Small Group
Projects, Self-study, etc.
ii) Evaluation: Tutorials, Class Tests, Presentations, Field work, Assignments, competency-
based Activity, Research papers, Term papers, etc.
The MCA programme is a combination of:
a. Three-Credit Courses (75 Marks each): 3 Credits each

b. Two-Credit Courses (50 Marks each): 2 Credits each
c. One-Credit Courses (25 Marks each) : 1 Credits each
Following are the session details per credit for each of L-P-T model
1) Every ONE-hour session per week of Lecture(L) amounts to 1 credit per semester,
2) Minimum of TWO hours per week of Practical(P) amounts to 1 credit per semester,
3) Minimum of ONE hours per week of Tutorial(T) amounts to 1 credit per semester
5. Open Courses (OC):
Institute has to offer two open courses of 1 credit each per semester to the students from Semester I
to Semester III. The motive behind keeping an open course is to make students aware of
current/upcoming trends in Information Technology and other domains. Full autonomy is given to the
Institute to plan and execute the open courses. It is expected to extend the autonomy to the student
also. Care must be taken to consider credit points and necessary contact hours assigned to it while
finalizing any open course for the given semester. In each semester total 2 credits are reserved for
open courses.
Suggestive List of OPEN Courses
FOR SEMESTER I FOR SEMESTER II FOR SEMESTER III

1 Data Privacy and Protection 1 Software Agent 1 Speech Recognition
2 Linux system administration 2 Aptitude building -1 2 Sentiment Analysis
3 social media listening 3 Basics of Tableau 3 R Programming
4 Research Methodology 4 Fraud detection 4 Gesture recognition
5 Applied Statistical Methods 5 Ruby Basics 5 Aptitude building-2
6 Digital Marketing 6 LaTeX 6 Digital Image processing
7 G-Suite 7 Big data Analytics 7 Network Security
8 Joomla 8 Game Programming in Unity 8 big data Technologies
9 e-trading 9 Block Chain Technology 9 AWS Fundamentals
Scratch and MIT App Business Intelligence - be
10
Inventor Programming 10 specific 10 Edge Computing
Random Forest using MS Design Thinking & Problem-
11
Excel 11 solving skills
12 WordPress 12 Green Computing
13 MS-OFFICE 13 IoT
14 Code ignitor
6. Extra Reading and Certification:
Each Chapter in the course is added with the extra reading part which gives extra pointer to gain
In-depth knowledge apart from basic knowledge imparted in the syllabus. Learners should be
encouraged to complete this extra reading portion as regular practice. Also, each course (Where
ever applicable) includes suggested certification which help learners to enrich themselves as per
industry demands and requirements.
7. Evaluation and Assessment:
In total 112 credits represent the workload of a year for MCA program.
Semester Credit IE UE
Semester I 28 350 350
Semester II 28 350 350
Semester III 28 350 350
Semester IV 28 350 350
Total 112 1400 1400
2800
The final total assessment of the candidate is made in terms of an internal (concurrent) evaluation and
an external (university) examination for each course. In total the internal (concurrent) to external
(university) marks ratio is maintained 50:50.
In general
1) For each course, 25 will be based on evaluation and 50 marks for semester end examination
conducted by University, unless otherwise stated.
2) The internal evaluation of 25 marks further divided into Written Examination (Assignments/Unit
test/written examination etc.), Practicals and Tutorials. The details have been specified in each
course.
3) There will be one Practical course and one Mini Project course in each semester with 75 marks
allotted for internal evaluation and 50 marks allotted for University examination. External
assessment will be done by university appointed examiner. During external examination, examiner
should ask the programs/practical ONLY from the work book of the students.
4) The internal marks will be communicated to the University at the end of each semester, but before
the semester-end examinations. These marks will be considered for the declaration of the results.
Guidelines to conduct Mini-Project evaluation for Semester I, Semester II and Semester III of MCA –
2020 pattern
For Internal Evaluation
1. Internal evaluation will be of 75 Marks. It will be distributed as follows
Description Marks
Project Report 35
Viva 15
Working Demo 25
Total 75
2. Project Report (including Project Diary) should be evaluated only during INTERNAL
evaluation. Textual chapters should be given 10 marks while diagrams, test
cases/validations, screen designs should be evaluated for 20 marks and 5 Marks should be
given for Project Diary. Thus, totaling up to 35 marks.
For External Evaluation
1. Evaluation will be conducted by one Internal (Appointed by Institute) and one External
examiner (Appointed by university).
2. External evaluation will be of 50 Marks. It will be distributed as follows
Description Marks
Viva 15
Working Demo 35
Total 50
For Internal Evaluation and External Evaluation

1. VIVA should be conducted based on project domain and technologies used for developing
the project. Every team member’s individual contribution to the project may vary. Hence
VIVA should be based on individual contribution pertaining to the project.
2. Working Demo is given maximum weightage to make sure that each group submits
executable version of their project.
3. Examiners should evaluate efforts and contribution of every individual in the team (in case
of group project).
4. Examiner may review code of the project while evaluating its working demo and modules.
Examination: Examinations shall be conducted at the end of the semester i.e. during November and in
April/May. However supplementary examinations will also be held in November and April/May.
Concurrent Evaluation: A continuous assessment system in semester system (also known as internal
assessment/comprehensive assessment) is spread through the duration of course and is done by the
teacher teaching the course. The continuous assessment provides a feedback on teaching learning
process. The feedback after being analyzed is passed on to the concerned student for implementation
and subsequent improvement. As a part of concurrent evaluation, the learners shall be evaluated on a
continuous basis by the Institute to ensure that student learning takes place in a graded manner.
Concurrent evaluation components should be designed in such a way that the faculty can monitor the
student learning & development and intervene wherever required. The faculty must share the
outcome of each concurrent evaluation component with the students, soon after the evaluation, and
guide the students for betterment Individual faculty member shall have the flexibility to design the
concurrent evaluation components in a manner so as to give a balanced assessment of student
capabilities across Knowledge, Skills & Attitude (KSA) dimensions based on variety of assessment tools.
Suggested components for Concurrent Evaluation (CE) are:
1. Case Study / Situation Analysis – (Group Activity or Individual Activity)

2. Class Test
3. Open Book Test
4. Field Visit / Study tour and report of the same
5. Small Group Project & Internal Viva-Voce
6. Learning Diary
7. Scrap Book
8. Group Discussion
9. Role Play / Story Telling
10. Individual Term Paper / Thematic Presentation
11. Written Home Assignment
12. Industry Analysis – (Group Activity or Individual Activity)
13. Literature Review / Book Review
14. Model Development / Simulation Exercises – (Group Activity or Individual Activity)
15. In-depth Viva
16. Quiz
Institute can decide the type, method and frequency of Concurrent Evaluation for each course and
execute accordingly. Detailed record of the Concurrent Evaluation shall be maintained by the Institute.
The same shall be made available to the University, on demand.
8. Choice based Credit System (CBCS) and Grading:
The detail document about Choice based Credit System for PG Programme is available on university
website. The Grading methodology is also available on university website. University reserves rights to
revise CBCS and grading system time to time.
9. Medium of Instruction:
The medium of Instruction will be English.
10.Clarification of Syllabus:
It may be necessary to clarify certain points regarding the course. The BOS should meet to study and
clarify any difficulties from the Institutes, as and when required.
11.Revision of Syllabus:
As the computer technology is changing very fast, revision of the syllabus should be considered every 2
years.
12.Attendance:
The student must meet the requirement of 75% attendance per semester per course for grant of the
term. The Director shall have the right to withhold the student from appearing for examination of a
specific course if the above requirement is not fulfilled. Since the emphasis is on continuous learning
and concurrent evaluation, it is expected that the student’s study all-round the semester. Therefore,
there shall not be any preparatory leave before the University examinations.
13.ATKT Rules:
The ATKT rules mention in CBCS handbook (available on university website) is application to MCA
Programme.
14.Maximum Duration for completion of the Programme:
The candidates shall complete the MCA Programme WITHIN 5 YEARS from the date of admission, by
earning the requisite credits. The student will be finally declared as failed if she/he does not pass in all
credits within a total period of four years. After that, such students will have to seek fresh admission as
per the admission rules prevailing at that time.
15.Structure of the Programme and detail syllabus of each course:

Semester I
Sr. No. Course Title Course Code CP EXT INT
1 Java Programming IT11 3 50 25
2 Data Structure and Algorithms IT12 3 50 25
3 Object Oriented Software Engineering IT13 3 50 25
4 Operating System Concepts IT14 3 50 25
5 Network Technologies IT15 3 50 25
6 Open Course 1 OC11 1 25
* Practicals
8 Practical IT11L 5 50 75
9 Mini Project ITC11 5 50 75
Soft Skills
10 Soft Skills - I SS11 1 25
28 350 350
Semester II
1 Python Programming IT21 3 50 25
2 Software Project Management IT22 3 50 25
3 Optimization Techniques MT21 3 50 25
4 Advanced Internet Technologies IT23 3 50 25
5 Advanced DBMS IT24 3 50 25
* Practicals
Soft Skills
10 Soft Skills - II SS21 1 25
28 350 350
Semester III
1 Mobile Application Development IT31 3 50 25
2 Data Warehousing and Data Mining IT32 3 50 25
3 Software Testing and Quality Assurance IT33 3 50 25
Knowledge Representation & Artificial
4 IT34 3 50 25
Intelligence - ML, DL
5 Cloud Computing IT35 3 50 25
* Practicals
Soft Skills
10 Soft Skills- III SS31 1 25
28 350 350
Semester IV
1 DevOps IT41 3 50 25
2 PPM and OB BM41 3 50 25
2 Project ITC41 22 250 300
28 350 350
Semester Credit IE UE
Semester I 28 350 350
Semester II 28 350 350
Semester III 28 350 350
Semester IV 28 350 350
Total 112 1400 1400
2800
Semester I
Course Code: IT-11
Course Name: Java Programming
Credit Scheme Evaluation Scheme
Lecture Practical Credit Internal External Total
Written Practical Tutorial
3 Hrs./Week - 3 25 - - 50 75
Course Description:
Prerequisite:
Knowledge of programming structures like decision flows, loops, etc.
Course Objectives:
1. To familiarize students with the concepts of OOPs.
2. To enable the students to understand the core principles of the Java Language and use
AWT tools to produce well designed, effective applications.
3. Students will be able to develop server-side applications with database handling using
servlets, JSP, JDBC
Course Outcomes:
Student will be able to
CO1 Understand Basic Concepts of OOPs, Java, Inheritance, Package. (Understand)
CO2: Understand Exception handling, arrays and Strings and multi-threading in Java
(Understand.)
CO3: Understand collection framework (Understand)
CO4: Develop GUI using Abstract Windows Toolkit (AWT) and event handling (Apply)
CO5: Develop Web application using JSP and Servlet, JDBC (Apply)
Course Structure:
Sr. No. Topics Details Weightage No of

in % Sessions
1 1. Introduction - 3 2
1.1 About Java
1.2 Flavours of Java
1.3 Java Installation
1.4 Java Program Development Environment
Extra reading: docs oracle docs

2 2. Object Oriented Programming 8 3
2.1 Class Fundamentals
2.2 Object & Object reference
2.3 Object Life time & Garbage Collection
2.4 Creating and Operating Objects
2.5 Constructor & initialization code block
2.6 Access Control, Modifiers, Use of Modifiers with
Classes & Methods.
2.7 Nested, Inner Class & Anonymous Classes,
Abstract Class & Interfaces
2.8 Methods, Defining Methods, Argument Passing
Mechanism, Method Overloading, Recursion,
Dealing with Static Members, Finalize ()
Method, Native Method.
2.9 Use of “this “reference,
2.10 Design of Accessors and Mutator
Methods
2.11 Cloning Objects, shallow and deep
cloning
2.12 Generic Class Types.
Extra Reading : OCA Java Programmer :I Exam Kathy

Sierra
3 3. Extending Classes and Inheritance 6 3
3.1 Use and Benefits of Inheritance in OOP
3.2 Types of Inheritance in Java
3.3 Inheriting Data members and Methods
3.4 Role of Constructors in inheritance
3.5 Overriding Super Class Methods, Use of “super”
3.6 Polymorphism in inheritance
3.7 Type Compatibility and Conversion
3.8 Implementing interfaces
Extra Reading: Understanding and practicing above

concept in depth - OCA Java Programmer: I Exam Kathy
Sierra
4 4. Package 3 2
4.1 Organizing Classes and Interfaces in Packages
4.2 Package as Access Protection
4.3 Defining Package
4.4 CLASSPATH Setting for Packages
4.5 Making JAR Files for Library Packages
4.6 Import and Static Import
4.7 Naming Convention for Packages.
Extra Reading: Oracle Java tutorial

5 5. Exception Handling 6 3
5.1 The Idea behind Exception
5.2 Exceptions & Errors
5.3 Types of Exception
5.4 Control Flow in Exceptions
5.5 JVM reaction to Exceptions
5.6 Use of try, catch, finally, throw, throws in
Exception Handling
5.7 In-built and User Defined Exceptions Checked
and Un-Checked Exceptions
Extra Reading: Oracle Java tutorial

6 6. Array & String: 4 2
6.1 Defining an Array
6.2 Initializing & Accessing Array
6.3 Multi –Dimensional Array
6.4 Operation on String, Mutable & Immutable
String
6.5 Using Collection Bases Loop for String,
Tokenizing a String
6.6 Creating Strings using StringBuffer, String
Builder
Extra Reading : Java arrays, tokenizer applications–

Jenkov Tutorials
7 7. Thread 6 3
7.1 Understanding Threads
7.2 Needs of Multi-Threaded Programming
7.3 Thread Life-Cycle
7.4 Thread Priorities
7.5 Synchronizing Threads
7.6 Inter Communication of Threads
7.7 Critical Factor in Thread –Deadlock
Extra Reading : Animation Using Thread

8 8. A Collection of Useful Classes 6 3
8.1 Utility Methods for Arrays
8.2 Observable and Observer Objects,
8.3 Date & Times,
8.4 Using Scanner
8.5 Regular Expression,
8.6 Input/output Operation in Java (java.io Package)
8.7 Streams and the new I/O Capabilities
8.7.1 Understanding Streams
8.7.2 The Classes for Input and Output
8.7.3 The Standard Streams
8.8 Working with File Object
8.8.1 File I/O Basics,
8.8.2 Reading and Writing to Files
8.8.3 Buffer and Buffer Management
8.8.4 Read/Write Operations with File
Channel
8.9 Serializing Objects
Extra Reading : regex – Pattern matching, split

examples, reading and writing Character Stream, Byte
stream and Objects in java files.
9. 9. UI Programming 12 5
9.1 Designing Graphical User Interfaces in Java,
9.2 Components and Containers,
9.3 Basics of Components
9.4 Using Containers
9.5 Layout Managers,
9.6 AWT Components
9.7 Adding a Menu to Window
9.8 Extending GUI Features Using Swing
Components
Extra Reading : Using Swing toolkit GUI –oracle java

tutorial
10 10. Event Handling 10 4
10.1 Event-Driven Programming in Java
10.2 Event- Handling Process
10.3 Event Handling Mechanism
10.4 The Delegation Model of Event Handling
10.5 Event Classes, Event Sources, Event Listeners
10.6 Adapter Classes as Helper Classes in Event
Handling.
Extra Reading : Hierarchy of Event Classes, Event

Sources, Event Listeners- Oracle java docs
11 11. The Collection Framework 10 4
11.1 Introduction to Java Frameworks
11.2 Collections of Objects
11.3 Collection Types, Sets, Sequence, Map
11.4 Understanding Hashing
11.5 Use of ArrayList & Vector
11.6 Java Utilities (java.util Package)
Extra Reading : searching, sorting, insertion,

manipulation, deletion of data using Java Collections
12 12. Database Programming using JDBC 10 4
12.1 Introduction to JDBC
12.2 JDBC Drivers & Architecture
12.3 CURD operation Using JDBC
12.4 Connecting to non-conventional
databases
Extra Reading: List of JDBC Drivers and Jars, Statement,
Prepared Statement and Callable Statement.
13 13. Java Server Technologies 16 7
13.1 Servlet Web Application Basics,
13.2 Architecture and challenges of Web
Application
13.3 Introduction to servlet
13.4 Introduction to JSP
13.5 Servlet life cycle
13.6 Developing and Deploying Servlets,
Exploring Deployment Descriptor
(web.xml)
13.7 Handling Request and Response.
Extra Reading : Session handling 4 methods, Request

Dispatcher ,JSP Tags, JSP Implicit objects, Generic
Servlet
Total: 100 45
Course References:
Recommended Books:
Text Books:
1. Java Complete Reference Schildt Herbert, TMH.
2. Java Fundamentals (SIE), Schildt Herbert, TMH
3. The Complete Reference JSP, Phil Hanna, TMH
4. JDBC, Servlet and JSP, Black Book, Santosh Kumar K. Dremtech publication
Reference Books:
1. Head First Servlets and JSP, 2nd Edition by Bert Bates, Bryan Basham, Kathy Sierra
2. OCJP Oracle Certified Programmer for Java Study Guide by Kathy Sierra and Bert
Bates.
3. A Programmer's Guide to Java OCJP Certification (A Comprehensive Primer) by
Khalid A. Mughal and Rolf W. Rasmussen.
4. Java Server Programming Java Ee&(J2EE 1.7), Black Book, Wiley publications
Recommended Learning Material:

1. www.javatpoint.com
2. www.oracle.com
3. www.tutorialspoint.com
4. www.geeksforgeeks.org/java
Recommended Certification:
1. OCA- Oracle Certified Associate
2. OCP- Oracle Certified Professional
Course Code: IT-12
Course Name: Data Structure and Algorithms
3 Hrs./Week - 3 25 - - 50 75
Course Description:
Prerequisite
Loops, Functions, Pointers, Arrays, Memory Allocation, Recursion
Course Objectives:
1. To understand basics data structure and algorithms
2. To solve problems using data structures such as linked lists, stacks, queues, hash tables,
trees, heaps and graphs
3. To understand various programming techniques such as brute force, greedy, dynamic
programming, divide-conquer and backtracking
Course Outcomes:
CO1: demonstrate linear data structures linked list, stack and queue (apply)
CO2: implement tree, graph, hash table and heap data structures (apply)
CO3: apply brute force and backtracking techniques (apply)
CO4: demonstrate greedy and divide-conquer approaches (apply)
CO5: implement dynamic programming technique (apply)
Course Structure:

in % Sessions
1 Linked List 8 2
1.1 Singly Linked List
1.2 Doubly Linked List
Extra Reading: Circular Linked list and Circular doubly

linked list
2 Stack and Queues 10 4
2.1 Linked List implementation of Stack
2.2 Linked List implementation of Queue
2.3 Circular Queue
2.4 Priority Queue
Extra Reading: Dqueue, Application of Stack
3 Tree 12 5
3.1 Tree
3.2 Binary Search Tree
3.3 AVL Tree
3.4 Red-Black Tree
3.5 Segment Tree - with min/max/sum range
queries
examples
3.6 Fenwick Tree (Binary Indexed Tree)
Extra Reading: Application of Tree, B* tree

4 Graph 8 2
4.1 Directed and Undirected Graph
4.2 Graph Representations
4.2.1 Adjacency Matrix
4.2.2 Adjacency List
4.3 Graph Traversals
4.3.1 BFS
4.3.2 DFS
Extra Reading: Application of Graph in Maps
5 Hash Table and Heaps 7 2
5.1 Hash Table
5.1.1 Hash Function
5.1.2 Hash function approaches
5.1.3 Handling the collisions
5.2 Heap
5.2.1 Min heap and Max heap
Extra Reading: Hashing used in File handling

6 Brute Force 10 5
6.1 Linear Search
6.2 Rain Terraces
6.3 Recursive Staircase
6.4 Maximum Subarray
6.5 Travelling Salesman Problem
6.6 Discrete Fourier Transform
Extra Reading: Application in Cryptography

7 Greedy 10 5
7.1 Jump Game
7.2 Unbound Knapsack Problem
7.3 Dijkstra Algorithm
7.4 Prim’s Algorithm
7.5 Kruskal’s Algorithm
Extra Reading: Huffman’s Tree
8 Divide and Conquer 10 8

8.1 Binary Search
8.2 Tower of Hanoi
8.3 Pascal's Triangle
8.4 Euclidean Algorithm
8.5 Merge Sort
8.6 Quicksort
8.7 Fast Powering
Extra Reading: Cooley–Tukey Fast Fourier Transform

(FFT) algorithm
9 Dynamic Programming 15 7
9.1 Fibonacci Number
9.2 Unique Paths
9.3 Longest Common Subsequence (LCS)
9.4 Longest Common Substring
9.5 Longest Increasing Subsequence
9.6 Shortest Common Super sequence
9.7 0/1 Knapsack Problem
9.8 Integer Partition
9.9 Regular Expression Matching
Extra Reading: Painting Fence Algorithm, Moser-de

Bruijn Sequence, Newman-Conway Sequence
10 Backtracking 10 5
10.1 Power Set
10.2 Hamiltonian Cycle
10.3 N-Queens Problem
10.4 Knight's Tour
10.5 Combination Sum
Extra Reading: Word Break Problem using Backtracking

Total: 100 45
Note: Course should be taught independent of any programming
language.
Course References:
Recommended Books:
Text Books
1. Jean Paul Tremblay, Paul G. Sorensons, “AN Introduction to Data Structures

with Application”, McGraw Hall Publication (INDIAN edition)
2. A. V. Aho and J.D. Ullman, “Design and Analysis of Algorithms”, Addison
Wesley
3. Thomas H Cormen and Charles E.L Leiserson, “Introduction to Algorithm” PHI
Reference Books
1. Lipschutz Schaum’s, “Data Structure”, Outline Series, MH

2. D. Samanta, “Classical Data Structure”, PHI,
3. Practical Approach to Data Structures by Hanumanthappa.
4. Data Structure and Algorithms in C++ by Joshi Brijendra Kumar
5. Data Structures with C++: Schaum’s Outlines by Hubbard JohnBressard,
6. Horowitz/Sahani, Fundamental of Algorithm. PHI, Galgotia.
7. Magnifying Data Structures, Arpita Gopal, PHI Publications
Course Code: IT-13
Course Name: Object Oriented Software Engineering
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Prerequisite:
Basic System Analysis and Design Concept
Course Objectives:
1. To study basic concepts of software engineering
2. To study phases of SDLC and different process models
3. To learn & understand the Requirement analysis and system Design.
4. To get acquainted with the agile software development methodology
Course Outcomes:
CO1: Distinguish different process model for a software development. (Understand)
CO2: Design software requirements specification solution for a given problem definitions of
a software system. (Analyze)
CO3: Apply software engineering analysis/design knowledge to suggest solutions for
simulated problems (Analyze)
CO4: Design user interface layout for different types of applications (Apply)
CO5: Recognize and describe current trends in software engineering (Understand)
Course Structure:

in % Sessions
1 1. Introduction to development approach SSAD and 10 4
OOAD
1.1. Overview of Software Development with SSAD
1.1.1. Basic System Development Life Cycle with
different users and their role in SDLC.
1.1.2. Different Approaches and Models for
System Development.
1.1.2.1. Waterfall Model
1.1.2.2. Spiral Model
1.1.2.3. Prototyping Model
1.1.2.4. RAD
1.1.2.5. Rational Unified Process
Extra Reading: Object oriented concepts

2. Requirement Engineering 20 9
2.1. Types of Requirements – Functional and Non-
functional
2.2. Four Phases of Requirement Engineering
2.3. Software requirement Specification (SRS)
2.3.1. Structure and contents of SRS
2.3.2. IEEE standard format for SRS
Note: Case studies based on SRS
Extra Reading: Fact finding techniques, Feasibility study

and reports
3. Use-case Driven Object-Oriented Analysis 40 20

3.1. Introduction to oops concepts
3.1.1. Class and object
3.1.2. Abstraction and encapsulation
3.1.3. Method and messages
3.1.4. Interface, Inheritance and polymorphism
3.1.5. Structural Diagram - Class Diagram and
Object diagram
3.1.6. Associations and links
3.1.7. Aggregation, Composition and containment
3.1.8. Inheritance, Sub Types and IS-A hierarchy
3.2. Behavioral Diagram

3.2.1. Use case Diagram
3.2.1.1. Identify Actors
3.2.1.2. Identify Use cases: describing how the
user will use the system
3.2.1.3. Develop use-case Model
3.2.1.4. Description of Use case Diagram.
3.2.2. Activity Diagram

3.2.3. Sequence diagram
3.2.4. Collaboration Diagram.
3.2.5. State Transition Diagram
Note: Case studies should be covered on the above topic
Extra Readings: UML diagram drawing tools such as

draw.io, Star UML, etc. , Documentation associated with
UML diagrams
4. User Interface Design 10 4
4.1. Elements of good design
4.2. Eight golden rules for design
4.3. Features of modern GUI, Menus, Scroll bars,
windows, buttons, icons, panels, error messages
etc.
Note: Case studies should be covered on the above topic
Extra Readings: UI/UX software, Interactive UI design

5. Current trends in Software Engineering 20 8
5.1. Introduction to Web Engineering
5.2. Agile Process
5.2.1. Agile Process Models
5.2.1.1. Extreme Programming (XP)
5.2.1.2. Adaptive Software Development (ASD)
5.2.1.3. Dynamic Systems Development
Method (DSDM)
5.2.1.4. Scrum
5.2.1.5. Crystal
5.2.1.6. Feature Driven Development (FDD)
Extra Readings: Comparative analysis of traditional

process models and agile, Agile methodology in testing
Total: 100 45
List of Practical (if any)
Case studies will be given to the student as a part of tutorial. The same diagram should be drawn using
UML diagram drawing tool as practical.
Course References:
Recommended Books:
Text Books:
1. Software Engineering by Roger Pressman (6th edition)
2. Object-Oriented Software Engineering: A Use Case Driven Approach by Ivan
Jacobson
3. Software Engineering by Sommerville, Pearson,8th Ed
4. Analysis & Design of Information System James Senn, TMH, 2nd Ed
5. Object Oriented System Development - Ali Bahrami McGraw-Hill International
Edition
6. Object-Oriented Software Engineering - Ivar Jacobson Pearson Education INC
7. Agile Software Engineering with visual studio by Sam Guckenheimer, Neno Loje.
8. UML Instant – Thomas A Pendar – Wiley Publication
9. UML in Nutshell, O’reilly Pub
Reference Books:
1. Software Requirements by Karl Wiegers

2. Object Oriented Modeling and Design with UML by James Rumbaugh, Michael
Blaha
3. Object Oriented Systems and Techniques with UML & Java by Udit Agarwal
4. Software Engineering by Chandramouli Subramanian, Saikat Dutt
5. Object Oriented Systems Analysis and Design using UML by Simon Bennett
6. UML 2 Bible by Tom Pender
7. The Unified Modeling Language user guide by Grady Booch, James Rumbaugh,
Ivar Jacobson
5. https://www.mooc-list.com/course/object-oriented-design-coursera
6. https://nptel.ac.in/courses/106101061/
Course Code: IT-14
Course Name: Operating Systems Concepts
3 Hrs./Week - 3 15 10 - 50 75
Course Description:
Prerequisite:
Basics of Operating System
Course Objectives:
1. To learn the fundamentals of Operating Systems and handle processes and threads and
their communication
2. To learn the mechanisms involved in memory management in contemporary OS
3. To know the functionality of Multiprocessor OS and Mobile OS.
4. To gain knowledge on distributed operating system concepts.
5. To learn about Basics of Linux.
6. To learn programmatically to implement Linux OS mechanisms.
Course Outcomes:
CO1: Understand structure of OS, process management and synchronization. (Understand)

CO2: Understand multicore and multiprocessing OS. (Understand)
CO3: explain Realtime and embedded OS (Understand)
CO4: understand Windows and Linux OS fundamentals and administration. (Understand)
CO5: solve shell scripting problems (Apply)
Course Structure:
Serial Topics Details Weightage No of

No. in % Sessions
1 1. Overview 15 7
1.1. Overview of operating systems
1.2 Functionalities and Characteristics of OS
1.3 Hardware concepts related to OS
1.4 CPU states
1.5 I/O channels
1.6 Memory Management
1.6.1 Memory Management Techniques
1.6.2 Contiguous & Non-Contiguous
allocation
1.6.3 Logical & Physical Memory –
Conversion of Logical to Physical address
1.7 Paging
1.7.1 Demand Paging
1.7.2 Page Replacement Concept
1.8 Segmentation - Segment with paging
1.9 Virtual Memory Concept
1.10 Thrashing
Extra Reading: Type of OS, Batch OS, Time Sharing OS,

Network OS, Multiprogramming OS, Multiprocessing
OS, Evolution of Operating System., Computer System
Organization Operating System Structure and
Operations- System Calls, System Programs, OS
Generation and System Boot
2 2. Process Management and Synchronization 17 8
2.1 PCB
2.2 Job and processor scheduling
2.3 Scheduling Concept
2.4 Process hierarchies
2.5 Problems of concurrent processes
2.6 Critical sections
2.7 Mutual exclusion
2.8 Synchronization
2.9 Deadlock
2.10 Device and File Management
2.10.1 Overview
2.10.2 Techniques
2.10.3 File Systems
Extra Reading: Threads- Overview, Multithreading

models, Threading issues, Process Synchronization –
The critical-section problem, Synchronization
hardware, Mutex locks, Semaphores, Classic problems
of synchronization, Critical regions, Monitors; Deadlock
– System model, Deadlock characterization, Methods
for handling deadlocks, Deadlock prevention, Deadlock
avoidance, Deadlock detection, Recovery from
deadlock., Banker’s Algorithms
3 3. Multiprocessor and Multicore Operating 17 8
Systems
3.1 Introduction
3.1.1 Advantages and Disadvantages
3.1.2 Multicore System Vs.
Multiprocessor System.
3.2 Types of Multiprocessors
3.2.1 Symmetric Multiprocessors
3.2.2 Asymmetric Multiprocessors
3.3 Basic Multicore Concepts: Memory Sharing
Styles
3.3.1 Uniform Memory Access (UMA)
3.3.2 Non-Uniform Memory Access
(NUMA)
3.3.3 No Remote Memory Access
(NORMA)
3.4 Cache Coherence, Inter-Process (and inter-
core) Communication:
3.4.1 Shared Memory
3.4.2 Message Passing
3.5 Mobile Operating Systems
3.5.1 Concept Need and Features
3.5.2 Types of Mobile OS
3.5.3 Overview of Android OS
3.5.4 Applications of Mobile OS
3.6 Distributed Operating Systems
3.6.1 Concept Need and Features
3.6.2 Examples of Distributed OS with brief
introduction
3.6.3 Applications of Distributed OS
Extra Reading: Virtual Machine, Cache Memory and

Catching Concept, Multi-Processor and Distributed
Operating System: – Introduction, – Architecture, –
Organization, – Resource sharing, – Load Balancing, –
Availability and Fault Tolerance, – Design and
Development Challenges, – Inter-process
Communication
4 4. Real Time OS 10 4
4.1 Introduction and use of RTOS
4.1.2 Components of RTOS
4.1.3 Types of RTOS
4.1.4 Features of RTOS
4.1.5 Factors for selecting in RTOS
4.1.6 Applications of RTOS
4.1.7 Disadvantages of RTOS
4.2 Embedded OS
4.2.1 Concept Need and Features of embedded
OS
4.2.2 Examples of embedded OS with brief
introduction
4.2.3 Applications of embedded OS
Extra Reading: Real Time and Embedded Operating

Systems: – Introduction, – Hardware Elements, –
Structure Interrupt Driven, Interrupt Driven,
Nanokernel, Nanokernel, Microkernel and Microkernel
and Monolithic kernel-based models. Monolithic
kernel-based models. – Scheduling – Periodic, Periodic,
Aperiodic and Aperiodic and Sporadic Tasks, Sporadic
Tasks, – Introduction to Energy Aware CPU Scheduling.
5 5.Windows OS and Windows Server 25 12
Architecture
5.1 Windows OS
5.1.1 Introduction
5.1.2 Windows OS Installation
5.1.3 Process Management
5.1.4 Control Panel Overview
5.1.5 Users, Security and Privacy Settings
5.1.6 Identify Accessibility Settings
5.1.7 Service Management
5.1.8 Syncing Devices and File Sharing
5.1.9Windows Utilities (Accessories, Disk
Management, Resource Monitor, Backup
and Recovery), Basic Troubleshooting
(Networking, Security, Device Driver).
5.2 Introduction to Ubuntu
5.2.1 Introduction
5.2.2 Overview of Kernel
5.2.3 Installation of Ubuntu
5.2.4 File system
5.2.5 Basic Commands of Linux
5.2.6 Managing Processes in Linux
5.2.7 Installing and deleting software
packages
5.2.8 User Management
5.2.9 File and Device Management
5.2.10 Backup and recovery
5.2.11 Introduction to Graphical
Environment (GNOME), Ubuntu Utilities
(VirtualBox, Evolution, Gimp, Bleach Bit,
Unity Tweak Tool etc.), SAMBA Overview
Extra Reading: Deploying and Managing Windows
Server 2012 and 2016, Introduction to Active
Directory Domain Services, Managing Active
Directory Domain Services Objects, Automating
Active Directory Domain Services Administration,
Implementing IPv4, Implementing DHCP,
Implementing DNS, Implementing Local Storage,
Implementing File and Print Services, Implementing
Group Policy.
6 6. Linux Shell Scripting 16 6
6.1 Introduction
6.2 Variables
6.3 Flow Controls
6.4 Loops
6.5 Functions
6.6 Lists
6.7 Manipulating Strings
6.8 Reading and Writing Files
6.9 Positional Parameters
6.10 Case statement
6.11Real time scripts for different system
administration activities
Extra Reading: Shell Script Programming Concepts,

Sequential Flow and Components of Shell Scripting,
Decision Structures, Decision-Structure Theory,
Statements & Operators, Looping Structures, Loop
Theory & Statements, Functions and Arrays, Functions
Parts/Libraries & Arrays, Advanced Shell Programming,
File Access, Sorts & Techniques, Advanced Tech & Tools
, Awk &Sed ,Script Design and Management Issues
Total: 100 45
List of Practicals (if any)
Minimum 5 Practicals to be conducted based on Shell Scripting
Course References:
Recommended Books:
Text Books:
1. “Operating System Concepts”, Abraham Silberschatz; Peter Baer Galvin; Greg

Gagne, Seventh Edition, John Wiley & Sons, 2004.
2. “Advanced Concepts in Operating Systems– Distributed, Database, and
Multiprocessor Operating Systems”, Mukesh Singhal and Niranjan G.
Shivaratri, Tata McGraw-Hill, 2001.
3. “Understanding the Linux kernel”, 3rd edition, Daniel P Bovet and Marco
Cesati, O’Reilly, 2005.
4. “Real-Time Systems: Theory and Practice”, Rajib Mall, Pearson Education
India, 2006.
5. “iPhone iOS 4 Development Essentials – Xcode”, Neil Smyth, Fourth Edition,
Payload
6. media, 2011.
7. “Microsoft Windows Server Administration Essentials”, Tom Carpenter
8. ”The Official Ubuntu Book” Eighth Edition, Matthew Helmke, Elizabeth K.
Joseph, José Antonio, Rey Philip Ballew, With Benjamin Mako Hill
Reference Books:
1. “ Operating Systems: Internals and Design Principles” by William Stallings.

2. “ Operating Systems: A Concept-Based Approach” by D M Dhamdhere.
3. System Concepts, 9th Edition, John Wiley & Sons, Inc. by Avi Silberschatz, Peter Baer
Galvin, Greg Gagne,
4. D.M Dhamdhere: Operating systems - A concept-based Approach, 3rd Edition, Tata
McGraw- Hill, 2012.
5. Operating Systems: Internals and Design Principles, 8th edition Pearson Education
Limited, 2014 by William Stallings.
6. Modern Operating system by Andrew Tenenbaum.
7. Distributed Operating System by Andrew Tanenbaum
8. P.C.P. Bhatt: Introduction to Operating Systems Concepts and Practice, 3rd Edition,
PHI, 2010.
9. Harvey M Deital: Operating systems, 3rd Edition, Pearson Education, 2011
Recommended Certification:
Windows Server certifications
1. Entry level: IT Infrastructure: Microsoft Technology Associate (MTA) certification.

2. Associate level: Windows Server 2016: Microsoft Certified Solutions Associate (MCSA):
Windows Server 2016 certification.
3. Associate level: Windows Server 2012: Microsoft Certified Solutions Associate (MCSA):
Windows Server 2012 certification.
4. Expert level: Server infrastructure: Microsoft Certified Solutions Expert (MCSE): Server
Infrastructure certification.
Linux Certifications
1. LINUX+ CompTIA
2. RHCE- RED HAT CERTIFIED ENGINEER
3. GCUX: GIAC CERTIFIED UNIX SECURITY ADMINISTRATOR
4. ORACLE LINUX OCA & OCP
5. LPI (LINUX PROFESSIONAL INSTITUTE) CERTIFICATIONS
LPIC- 1: Linux Administrator

LPIC- 2: Linux Engineer
LPIC- 3: Linux Enterprise Professional Certification
Course Code: IT-15
Course Name: Network Technologies
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Prerequisite:
Students should have fundamental knowledge of computer network.
Course Objectives:
1. To understand various computer networks and technologies behind networks

2. To study TCP/IP protocol suite, IP addressing schemes and link layer communication
3. To study routing concept along with Routing protocols
4. To study application layer protocols
5. To understand basics of cryptography and socket programming
Course Outcomes:
CO1: Understand the basic concepts of Computer Network, and principle of layering
(Understand)
CO2: Apply the error detection and correction techniques used in data transmission (Apply)
CO3: Apply IP addressing schemes and sub netting (Apply)
CO4: Understand the concept of routing protocols, Application layer protocols and Network
Security (Understand)
CO5: Apply the socket programming basics to create a simple chat application
(Apply)
Course Structure:

in % Sessions
1 1. Introduction to Data Communication and
Computer Networks 6 3
1.1. Internet basics and network components.
[Transmission Media-Guided, Unguided,
Network Devices]
1.2. Various types of Networks (only overview)
1.2.1. Connection Oriented N/Ws Vs
Connectionless N/Ws,
1.2.2. Ethernet- Ethernet standards ZigBee,
WiFi, Access Technique -CSMA-CD,
Negotiation technique Overview
1.2.3. Wireless Network
1.3 Unified Communication –VOIP
Extra Reading: Switching Techniques, CSMA/CA,
CSMA/CD, Unified Communication
2 2. Principle of Layering concept 12 8

2.1 Need for layering
2.2 ISO-OSI 7 Layer Model
2.3 TCP/IP model
2.4 OSI Model vs TCP/IP mode
Extra Reading: Data Encapsulation, PDU Formation,

network devices
3 3. Link Layer Communication 25 10
3.1 Error detection and correction techniques
3.2 Framing and its types
3.3 Flow and error control
3.4 HDLC protocol
3.5 P2P Protocol
Note: Examples based on 3.1 to be covered
Extra Readings: DLL protocol examples, IEEE 802.2 MAC

protocol
4 4. IP Addressing 25 10
4.1 Internet Protocol and IPv4 Packet format,
4.2 Addressing, Physical Addresses, Logical
Addresses
Port Addresses, Specific Addresses
4.3 IP Address- Network Part and Host Part
4.4 Network Masks, Network Addresses and,
Broadcast
Addresses, Loop Back Address
4.5 Address Classes
4.6 TCP and UDP Connections
4.7 TCP Performance in wireless network
4.8 Overview of IPv6
4.9 IP Routing - Types of routing protocol, Border
Gateway Protocol (BGP), Routing Information
Protocol (RIP), Open Shortest Path First (OSPF),
Routing Table concept
Notes: Examples based on IP addressing and sub
netting to be covered
Extra Reading: Network Monitoring Tools –Open NMS,
Putty, Wireshark, Nagios core, Cacti
5 5. Application Layer Protocols 15 6
5.1 DHCP – DHCP Client, DHCP server, DHCP scope
5.2 DNS – Resolution process, Resource Records,
DNS protocol structure
5.3 HTTP – WWW architecture, HTTP: Request and
Response Message
5.4 Email protocols – SMTP, POP3, IMAP4 & MIME
5.5 FTP, Telnet
Extra Reading: Practical on FTP, Telnet, DNS, Putty

6 6. Network Security 5 2
6.1Active and Passive attacks
6.2Cryptography (Symmetric and Asymmetric)
6.3Firewall
Extra Reading: Examples on symmetric and asymmetric

algorithms
7 7. Socket Programming 12 6
7.1 Introduction
7.2 Berkeley Sockets
7.3 Specifying A Protocol Interface
7.4 The Socket Abstraction
7.4.1 System Data Structures for Sockets
7.5 Specifying an Endpoint Address
7.6 A Generic Address Structure
7.7 Major System Calls Used with Sockets
7.8 Utility Routines for Integer Conversion
7.9 Using Socket Calls in A Program
(The socket can be created in any language)
Extra Reading: Client-Server Architecture and its

implementation using Socket programming
Total: 100 45
List of Practical assignments (Socket Programming):

1. Write the client and server programs for establishing termination of connection
between client and server using TCP. Assume the server can handle only one client.
2. Write the client and server programs for simple data (hello) transfer between client and
server using UDP. Client will send hello server message to the server program. In its
reply the server will send hello client message. The server and client programs should
reside on different computers in a network.
3. Write the client and server programs for connectionless communication between two
different computers in the same TCP/IP network. The server process receives a byte
from the client process should and send back an should acknowledgement to the client
process.
4. Write program for implementing the sliding window protocol of window size 5.
5. Write the client and server program for implementing the broadcasting in the local
network.
Course References:
Recommended Books:
Text Books:
1. Network Essential Notes GSW MCSE Study Notes

2. Internetworking Technology Handbook CISCO System
3. Data and Computer Communication 8th Edition – William Stallings
4. Official Certification guide CCNA 200-301
5. TCP/IP Sockets in JAVA, Practical Guide for Programmers, Kenneth L Calvert,
Michael J Donahoo
Reference Books:
1. Data Communication and Networking Behroz A.Forouzan, TMH, 4th Edition
2. Computer Networks and Internets with Internet Applications Douglas Comer
3. Cryptography and Network Security Atul Kahate, TMH 2nd Edition
4. Internetworking With TCP/IP Vol III: Client-Server Programming and Applications
BSD Socket Version Second Edition
1. https://docs.oracle.com.javase/tutorial/networkingindex.html
2. https://docs.oracle.com/javase/tutorial/networking/overview/networking.html
Recommended Certifications:
1. CISCO Networking Basics Specialization (Coursera) -

2. Network Protocols and Architecture (Coursera)
3. Data Communications and Network Services (Coursera)
4. Computer Networking-Digital Network Security (www.alison.com/course)
5. CCNA (200-301)
6. CCNP Enterprise (300-401 ENCOR)
7. CCNP Security (300-700 SCOR +concentration exam)
8. CCIE Enterprise Infrastructure(300-401 ENCOR + Infrastructure lab v1.0)
9. CCIE Enterprise Wireless CCIE +(300-401 ENCOR +wireless lab v1.0)
10. Microsoft Networking Fundamentals (98-366)
11. Microsoft Security Fundamentals (98-367)
Course Code: IT-11L
Course Name: Practicals
- 10 Hrs./Week 5 - 75 - 50 125
Course Description:
This Practical course contains 3 sections. –
1. JavaScript Syllabus
2. GITHUB Syllabus (Not for Evaluation)
3. List of Practicals – Java Programming
4. List of Practicals – Data Structure and Algorithm
Course Outcomes:
CO1: Demonstrate Collection framework (Apply)

CO2: Develop GUI using awt and swing (Apply)
CO3: Develop Web application using JSP and Servlet, JDBC (Apply)
CO4: Apply Data Structure to solve problems using JavaScript (Apply)
Course Structure:
Syllabus for JavaScript
Sr. No. Topics Details
1 Introduction to JavaScript - History, Features, Application of JavaScript,

JavaScript Basics –Data Types, Variables, Identifiers, Constants, Comments,
Operators in JavaScript
2 Control and looping structure
3 Array – Concept, Types and Methods
4 Java Script Objects – Object ,Date ,String, Array , Math, Number, Boolean
5 Event handling-Mouse, Keyboard, Form, Window
6 JavaScript BOM –Browser object, Window, Location, Navigator, History Object
7 JavaScript DOM –Document Object and its Methods
8 Form Validations in JavaScript
9 Exception Handling in JavaScript using JavaScript
Syllabus for GIT/GITHUB
Sr. No. Topics Details
1 Introduction to versioning systems

2 creating repositories [local & cloud based]
3 git commands
4 branching & merging
5 conflict resolution (3-way merge)
6 rebasing
7 version control [tagging]
Session on GIT/GITHUB is not for evaluation. It may be conducted by using

Demonstration method. The objective of these sessions is “Students must able to submit
their mini-project on GITHUB as project repositories”
List of Practicals – Java Programing
1. Installation of jdk enviorment & following utilities. What is javac , javap and javadoc.
2. Design an application by using array.
3. Implementation of package, Interface and abstract class
4. Design application using String, StringBuilder, StringTokenizer
5. Test any five of standard exception and user Defined Custom Exceptions in java
6. Threads creation and design applications by using Extending the Thread class/ Implementing
the Runnable Interface. Application of multithreading in java.
7. Design java application using Collection in java such as Array List, Link List
8. Design GUI based java application using AWT, Swing with Event Handling.
9. Design a and implement JDBC applications.
10. Design and implement servlet applications.
11. Design and implement JSP applications
List of Practicals – Data Structure and Algorithm Practicals
Following practical must be implemented using JavaScript
1. Demonstrate singly and doubly linked list

2. STACK implementation using Array with PUSH, POP operations
3. Reverse a string using stack
4. Check for balanced parentheses by using Stacks
5. Implement Stack using Linked List
6. Demonstration of Linear Queue, Circular Queue, Priority Queue
7. Reverse stack using queue
8. Practical based on binary search tree implementation with its operations
9. Graph implementation and graph traversals
10. Implementation of Hashing
11. Practical based on Brute Force technique
12. Practical based on Greedy Algorithm-Prim’s/Kruskal’s algorithm
13. Practical based on Divide and Conquer Technique-Binary Search, Tower of Hanoi
14. Implementation of Dynamic Programming- LCS, Regular Expression Matching
15. Practical based on backtracking- N Queen’s problems
Course Code: ITC11
Course Name: Mini Project
- 10 Hrs./Week 5 - 75 - 50 125
Course Description:
A mini project is an assignment that the student needs to complete at the end of every semester to
strengthen the understanding of fundamentals through effective application of the subjects learnt.
Course Outcomes:
CO1: Create working project using tools and techniques learnt in this semester (Create)
Course Structure:
Guidelines for Mini Project
1. Students are expected to undertake one mini project starting from first semester till third
semester.
2. The student may take up the mini project in first semester based on the courses learnt in that
semester and for every next semester the mini project may be based on the courses learnt in
the current semester along with all the subjects learnt in earlier semesters.
3. The student may take up the project individually or in group. However, if project is done in
group, each student must be given a responsibility for distinct modules.
4. Selected project/module must have relevant scope as per the marks assigned and must be
carried out in the Institute.
5. Internal guide should monitor and evaluate the progress of the project on individual basis
through handwritten workbook (Project Diary) maintained by students containing various
project milestones with learnings and remarks from internal guide for concurrent evaluation.
6. The Project Synopsis should contain an Introduction to Project clearly stating the project scope
in detail justifying enough scope for 125 marks. The project work will carry 75 marks for internal
assessment and 50 marks for external assessment.
7. Students are expected to show working demo of the project during final evaluation.
8. Students are expected to upload mini-project on GITHUB as project repository of the
institution.
9. Students are expected to submit the soft copy of mini project report as a part of final
submission.
10. The project will be assessed internally as well as externally by the examiners appointed by
University. University may appoint Industry Experts as an external examiner
Semester II
Course Code: IT-21
Course Name: Python Programming
3 Hrs./Week - 3 25 - - 50 75
Course Description:
Prerequisite:
Object oriented Concepts.
Course Objectives:
1. To understand and use the basic of python.
2. To understand advance concepts of python and able to apply it for solving the complex
problems.
3. To understand the reading and writing data through file handling.
4. To understand basic database concepts in python.
5. To develop the critical thinking and analytical approach by using python libraries.
Course Outcomes:
CO1: Understand Demonstrate the concepts of python and modular programming.
(Understand)
CO2: Apply the concepts of concurrency control in python (Apply)
CO3: Solve the real-life problems using object-oriented concepts and python
libraries (Apply)
CO4: Demonstrate the concept of IO, Exception Handling, database (Apply)
CO5: Analyze the given dataset and apply the data analysis concepts and data
visualization. (Analyze)
Course Structure:
Unit Topics Details Weightage No of

No. in % Sessions
1 1. Introduction & Components of Python 15 7
1.1. Understanding Python
1.2. Role of Python in AI and Data science
1.3. Installation and Working with Python
1.4. The default graphical development environment for
Python - IDLE
1.5. Types and Operation
1.6. Python Object Types-Number, Strings, Lists,
Dictionaries, Tuples, Files, User Defined Classes
1.7. Understanding python blocks
1.8. Python Program Flow Control
1.9. Conditional blocks using if, else and elif
1.10. Simple for loops in python
1.11. For loop using ranges, string, list and
dictionaries
1.12. Use of while loops in python
1.13. Loop manipulation using pass, continue,
break and else
1.14. Programming using Python conditional and
loops block
Extra Reading: Python installation with windows, Linux and

MAC OS, creating virtual environment, configuring python
on EC2 instance, understanding python IDE –[ VSCode,
PyCharm, Spyder], Installing Anaconda and setting up
environment for python
2 2. Python Functions, Modules & Packages 15 7
2.1. Function Basics-Scope, nested function, non-local
statements
2.2. built-in functions
2.3. Arguments Passing, Anonymous Function: lambda
2.4. Decorators and Generators
2.5. Module basic usage, namespaces, reloading
modules. – math, random, datetime, etc.
2.6. Package: import basics
2.7. Python namespace packages
2.8. user defined modules and packages
Extra Readings: GUI framework in python

3 3. Python Object Oriented Programming 15 6
3.1. Concept of class, object and instances, method call
3.2. Constructor, class attributes and destructors
3.3. Real time use of class in live projects
3.4. Inheritance, super class and overloading operators,
3.5. Static and class methods
3.6. Adding and retrieving dynamic attributes of classes
3.7. Programming using OOPS
3.8. Deligation and container
Extra Readings: Integrating GUI framework with OOP

4 4. Python Regular Expression 10 4
4.1. Powerful pattern matching and searching
4.2. Power of pattern searching using regex in python
4.3. Real time parsing of data using regex
4.4. Password, email, URL validation using regular
expression
4.5. Pattern finding programs using regular expression
Extra Readings: Web scrapping and pattern matching with
regex
5 5. Python Multithreading and Exception Handling 10 5
5.1. Exception Handling
5.2. Avoiding code break using exception handling
5.3. Safe guarding file operation using exception
handling
5.4. Handling and helping developer with error code
5.5. Programming using Exception handling
5.6. Multithreading
5.7. Understanding threads
5.8. Synchronizing the threads
5.9. Programming using multithreading
Extra Readings: Multiprocessing, deadlock, synchronization,

monitors and messaging queue
6 6. Python File Operation 5 2
6.1. Reading config files in python
6.2. Writing log files in python
6.3. Understanding read functions, read(), readline() and
readlines()
6.4. Understanding write
6.5. functions write() and writelines()
6.6. Manipulating file pointer using seek
6.7. Programming using file operations
Extra Readings: Reading and writing the files on AWS S3

bucket
7 7. Python Database Interaction 10 5
7.1. Introduction to NoSQL database
7.2. Advantages of NoSQL database
7.3. SQL Vs NoSQL
7.4. Introduction to MongoDB with python
7.5. Exploring Collections and Documents
7.6. Performing basic CRUD operations with MongoDB
and python
Extra Readings: Graph database like Neo4j with python

8 8. Python for Data Analysis 20 9
8.1. NumPy:
8.2. Introduction to NumPy
8.3. Creating arrays, Using arrays and Scalars
8.4. Indexing Arrays, Array Transposition
8.5. Universal Array Function
8.6. Array Input and Output
8.7. Pandas:
8.8. What are pandas? Where it is used?
8.9. Series in pandas, pandas DataFrames, Index objects,
ReIndex
8.10. Drop Entry, Selecting Entries
8.11. Data Alignment, Rank and Sort
8.12. Summary Statics, Missing Data, Index
Hierarchy
8.13. Matplotlib:
8.14. Python for Data Visualization
8.15. Introduction to Matplotlib
8.16. Visualization Tools
Extra Readings: Text analytics with NLP and python

Total: 100 45
Course References:
Recommended Books:
Text Books:
Introduction to Python Programming, By Gowrishankar S, CRC Press
Reference Books:
1. Learning Python 5th ed. by Mark Lutz

2. Python: The Complete Reference by Martin C. Brown
3. Python Data Analytics: With Pandas, NumPy, and Matplotlib 2nd ed. Edition by
Fabio Nelli
4. Core Python Programming by Wesley J. Chun Publisher: Prentice Hall
5. Python Programming: A modular approach by Taneja Sheetal, Kumar Naveen
6. Beginner's Guide to Python Programming: Learn Python 3 Fundamentals,
Plotting and Tkinter GUI Development Easily by Serhan Yamacli
7. Programming Python, O’reilly, by Mark Lutz
8. Learning Python, O’reilly, Mark Lutz
9. Head First Python, O’reilly, By Paul Barry
1. Programming, Data Structures and Algorithms Using Python

https://swayam.gov.in/nd1_noc19_cs40/preview
2. Data Analytics with Python https://swayam.gov.in/nd1_noc20_cs46/preview
Course Code: IT-22
Course Name: Software Project Management
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Prerequisite:
Basic Software Engineering process
Course Objectives:
1. To learn process of Software Project Management.
2. To Study role of Project Manager in Project Management.
3. To learn Agile Project Management Framework.
4. To study various role of Agile Team and Tools.
5. To understand project planning and tracking.
Course Outcomes:
CO1: Understand the process of Software Project Management Framework and
Apply estimation techniques. (Apply)
CO2: Learn the philosophy, principles and lifecycle of an agile project. (Understand)
CO3: Demonstrate Agile Teams and Tools and Apply agile project constraints and
trade-offs for estimating project size and schedule (Apply)
CO4: Explain Project Tracking and Interpretation of Progress Report (Understand)
CO5: Analyze Problem statement and evaluate User Stories (Analyze)
Course Structure:

in % Sessions
1 1. Linear Project Management Framework 15 6
1.1 Overview of project Management
1.2 Project management life cycle-IEEE Life Cycle
1.3 Project Management Process
1.4 Role of Project Manager
1.5 Quality Metrics
1.6 Risk Management Process (Case Study Based)
1.6.1 Risk Identification
1.6.2 Risk Analysis
1.6.3 Risk Mitigation
1.6.4 RMMM
1.7 Hands on MS Project Tool– Resource
Allocation, Scheduling, Gannt chart
Note: Case studies based on Risk Management, MS

Project tool & Gannt Chart
Extra Reading: Different software project

management, Types of Risk, Risk Information sheet
(RIS), CPM and PERT
2 2. Linear Software Project Estimation 20 8

2.1 Different methods of Cost estimation
2.1.1 COCOMO-I & II model (Problem
Statement)
2.1.2 Delphi cost estimation
2.2 Function Point Analysis (Problem Statement)
2.3 The SEI Capability Maturity Model CMM
2.4 Software Configuration management
Note: Case studies/Numerical Problems based on
COCOMO-I and FPA
Extra Reading: KLOC, Rayleigh Curve, Change
Management, Configuration management tool - SVN
Tool or Redmine
3 3. Agile Project Management Framework 15 10

3.1 Introduction and Definition Agile, Agile
Project Life Cycle
3.2 Agile Manifesto: History of Agile and Agile
Principles
3.3 Key Agile Concepts:
3.3.1 User stories, Story points
3.3.2 Product Backlog
3.3.3 Sprint Backlog,
3.3.4 Sprint Velocity
3.3.5 Swim lanes
3.3.6 Minimum Viable Product (MVP)
3.3.7 Version and Release
3.4 Agile Project Management v/s Traditional
Project Management
Note: Case studies based on agile vs. traditional
project
Extra Reading: Study Scrum Agile Framework, Agile

project management delivery & methodology
framework, Software project team management and
different team structures
4 4 Agile Teams, Size and Schedule 15 10

4.1 Dynamic System Development Method
4.2 Value-Driven Development
4.3 Team and roles of an Agile Team
4.3.1 Scrum Master
4.3.2 Product Owner
4.3.3 Development Team
4.4 Product Vision and Product Roadmap
4.5 Project Objective and Key Metrics
4.6 Introduction to User Stories
4.7 Estimate the Product Backlog
4.8 Techniques for estimating Story Points
4.9 Plan Product Releases
4.10 Product Prioritization
Note: Case studies based on Estimation of Product

backlog & Story points, design your team and Add
screenshots with the caption, Design User stories, log
efforts and task in detail
Extra Reading: Personnel Management, Release &
iteration planning, eXtreme Programming (XP), Values
and Principles, Team Dynamics and Collaboration
5 5.Tracking Agile Project and Reports 20 5

5.1 Introduction
5.2 Plan and Execute Iteration
5.3 Facilitate Retrospective, Making Team
Decisions and Closing out Retrospective
5.4 Agile Reports
5.4.1 Daily Reports
5.4.2 Sprint Burn down Chart and Reports
5.5 Benefits of Agile Project Management
Note: Case studies based on No. of iterations and

Project Report, Sprint Chart
Extra Reading: Use of MS Project to track agile
project, Agile project management tools, Feature-
Driven Development, Agile Metrics
6 6. Implementation with Agile Tools 15 6

6.1 Introduction of Agile Tools
6.2 Hands on GitHub
6.2.1 Create Project using Kanban
6.2.2 Project Repositories
6.2.3 Continuous Integration
6.2.4 Project Backlog
6.2.5 Team Management
6.2.6 Progress Tracking
6.2.7 Releases
6.3 Implementation of Problem statement with
Agile Tools- GitHub
6.3.1Designing Product Vision, Product
Backlog,
6.3.2 Sprint Backlog, Estimate Story Points
6.3.3 Iteration Release
Note: Case study on design of product vision &

backlog with features and user stories, Estimation of
story points, Design Iteration Plan, Iteration progress
and close iteration in detail
Extra Reading: Agile modeling, Explore various Agile
Tools
Total: 100 45
List of Practical’s (if any)
1. Design Project Management plan template by using MS-Project tool. (Resource allocation,
Scheduling, Cost Calculation and Gantt Chart)
2. Create project plan using agile methodologies for the development of web page of Library
Management System as a minimum viable product using 3 resources as per sprint planning.
3. Calculate the effort to execute the task and prioritize the task to execute in the current
sprint and keep rest of the task in backlog.
4. Demo of the task developed by the developer in the Sprint.
5. Retrospective to discuss about the short coming and improvement of the design and
execution of the Sprint task.
6. Check in the developed code in the GitHub repository.
Course References:
Recommended Books:
Text Books:
1. Software engineering principles and practice, McGraw-Hill, Waman S.
Javadekar
2. Software Engineering by Pressman
3. Agile Project Management for Dummies, 2nd Edition
4. Coaching Agile Teams: A Comparison for ScrumMasters, Agile Coaches,
and Project Managers in Transition, Lyssa Adkins
5. Agile Project Management: Creating Innovative Products (2nd Edition) by
Jim Highsmith, Addison-Wesley Professional
Reference Books:
1. Mark C. Layton, Steven J. Ostermiller

2. Agile Estimating and Planning by Mike Cohn Robert C Martin Series
3. Introduction to Software Project Management by Adolfo Villafiorita, CRC
Press
4. Agile Project Management with Scrumby Ken Schwaber, Microsoft Press ©
2004
5. Agile Project Management QuickStart Guide : The Simplified Beginners
Guide to Agile Project Management by ClydeBank Business
6. Agile Product Management with Scrum: Creating Products that Customers
Love by Roman Pichler.
7. Scrum Mastery: From Good to Great Servant-Leadership by Geoff Watts
8. Agile Project Management for Dummies by Mark C. Layton
9. The Agile Enterprise: Building and Running Agile Organizations by Mario E.
Moreira
10. Scrum: The Art of Doing Twice the Work in Half the Time by Jeff
Sutherland
11. Essential Scrum: A Practical Guide to the Most Popular Agile Process by
Kenneth S. Rubin
12. Agile Project Management with Kanban By Eric Brechner
13. Agile Constraints: Creating and Managing Successful Projects with Scrum,
Multiple authors
1. https://learning.tcsionhub.in/
2. https://www.agilealliance.org
3. http://www.pmi.org
4. https://github.com/topics/kanban
5. https://www.opensourcescrum.com/
6. https://www.scrum.org/resources
7. https://www.tutorialspoint.com/agile/index.htm
8. https://www.atlassian.com/agile
9. https://www.javatpoint.com/agile
10. https://www.guru99.com/agile-testing-course.html
11. https://www.visual-paradigm.com/tutorials/agile-tutorial/
1. Project Management Professional (PMP)

2. PMI-ACP(Agile Certified Practitioner)
3. Associate in Project Management
4. BVOP Certified Project Manager
5. Certified Associate in Project Management (CAPM)
6. Certified Project Director
7. Certified Project Management Practitioner (CPMP)
8. Certified Project Manager (CPM)
9. Certified ScrumMaster (CSM)
10. CompTIA Project+
11. Master Project Manager (MPM)
12. PRINCE2 Foundation/PRINCE2 Practitioner
13. Professional in Project Management (PPM)
14. Project Management in IT Security (PMITS)
15. APMG International
16. Strategyex Certificate (Associate or Master’s) in Agile
17. International Consortium for Agile (ICAgile)
18. Agile Certification Institute
19. Scaled Agile Academy
20. Scrum Alliance
21. Certified Agile Project Manager (IAPM)
Course Code: MT-21
Course Name: Optimization Techniques
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Prerequisite:
Basic mathematical knowledge is essentials.
Course Objectives:
1. To understand the role and principles of optimization techniques in business world.
2. To understand the process of problem statement formulation of the business scenario.
3. To understand the implementation of various decision-making techniques in the process of
decision making.
4. To gain the techniques and skills on how to use optimization techniques to support the
decision making in business world.
Course Outcomes:
CO1: Understand the role and principles of optimization techniques in business world
(Understand)
CO2: Demonstrate specific optimization technique for effective decision making (Apply)
CO3: Apply the optimization techniques in business environments (Apply)
CO4: Illustrate and infer for the business scenario (Analyze)
CO5: Analyze the optimization techniques in strategic planning for optimal gain. (Analyze)
Course Structure:

in % Sessions
1 1. Linear Programming 20 10
1.1. Various definitions, statements of basic
theorems and properties, Advantages and
Limitations,
1.2. Application areas of Linear programming
1.3. Linear Programming – Concept
1.4. Simplex Method and Problems
1.5. Two Phase Simplex Method and problems,
Note: Case study-based problems

Extra Readings: Formulation of Linear programming,
Solution of LPP using Graphical method
2 2. Markov Chains & Simulation Techniques: 15 7
2.1 Markov chains: Applications related to
technical
functional areas,
2.2 Steady state Probabilities and its implications,
2.3 Decision making based on the inferences
Monte Carlo Simulation.
Extra Readings: Application of Markov chain in

Queuing theory, Simulation techniques used in
Machine learning and bioinformatics
3 3. Sequential model and related Problems 15 6
3.1 Processing n jobs through 2 machines
3.2 Processing n jobs through 3 machines
3.3 Processing n jobs through m machine
Extra Readings: Processing of n jobs through m

machines
4 4. PERT & CPM 20 10
4.1 Basic differences between PERT and CPM.
4.2 Network diagram
4.3 Time estimates (Forward Pass Computation,
Backward Pass Computation
4.4 Critical Path
4.5 Probability of meeting scheduled date of
completion,
4.6 Calculation on CPM network.
4.7 Various floats for activities
4.8 Event Slack
4.9 Calculation on PERT network.
4.10 Application of schedule based on cost
analysis and crashing
4.11 Case study-based problems
Extra Readings: Optimal Cost estimation by crashing

the network, Explore the MS Project tool.
5 5. Game Theory 15 6
5.1 Introduction
5.2 n X m zero sum game with dominance
5.3 Solution using Algebraic, Arithmetic and
Matrix strategy
Extra Readings: Learn the difference between

Sequential and Simultaneous game
6 6. Decision Analysis 15 6
6.1 Introduction to Decision Analysis
6.2 Types of Decision-making environment
6.3 Decision making under uncertainty and under
risk
6.4 Concept of Decision Tree
Extra Readings: Decision models in Econometrics and

computer science
Total: 100 45
Practicals to be conducted on the following topics. It is expected that, Applications to be covered

using Python and /or R.
1. Linear Programming
2. Markov Chain and Simulation Techniques
3. Sequential models and related problems
4. CPM and PERT
5. Game Theory
6. Decision Analysis
Course References:
Recommended Books:
Text Books:
1. Operations Research by Pannerselvam
2. Operations Research Theory and Application by J. K. Sharma –Mac-Millan
Publication
3. Statistical and Quantative Methods – Mr. Ranjit Chitale
Reference Books:
1. Statistical Methods – S.P.Gupta, Sultan Chand, New Delhi

2. Operation Research by V. k. Kapoor
3. Operations Research by Kanti Swaroop, P. K. Gupta and Man Mohan
4. Introduction to Operations Research by Hiller & Lieberman, Tata Mc Graw
Hill
5. Operations Research by H. A. Taha
6. Operation Research by Hira & Gupta
7. What is Game Theory?, David K. Levine, Economics, UCLA
8. Recommended Learning Material:
Research Software:
1. MS Excel Solver
2. TORA
3. Python and / or R programming
Websites:
1. www.orsi.in
2. www.atozoperationalresearch.com
Websites for practical sessions:

1. https://towardsdatascience.com/linear-programming-and-discrete-
optimization-with-python-using-pulp-449f3c5f6e99
2. https://github.com/topics/operations-research?l=python
3. https://github.com/Gabeqb/Linear-Programming-With-
Python/commit/a61be0d5fc8e66dd38f3d094bb80cef6a9a04152
Journals:
1. International Journal of Operations Research and Management science
2. International Journal of Operations and Quantitative Management
3. Indian Journal of Advance Operations Management.
1. Data science with Python

2. Data science with R programing
3. Certification in Machine Learning
4. Certification in Tableau
Course Code: IT-23
Course Name: Advanced Internet Technologies
3 Hrs./Week - 3 25 - - 50 75
Course Description:
Prerequisite:
Student must have hands-on working knowledge of HTML, CSS, JavaScript and Angular JS
Course Objectives:
1. To impart the design, development and implementation of Dynamic Web Pages.
2. To implement the Latest properties of CSS3
3. To implement the Concept of NodeJS.
4. To develop programs for Web using Angular and SPA.
5. To design and implement dynamic websites with good sense of designing and latest
technical aspects.
Course Outcomes:
CO1: Outline the basic concepts of Advance Internet Technologies (Understand)
CO2: Design appropriate user interfaces and implements webpage based on given
problem Statement (Apply)
CO3: Implement concepts and methods of NodeJS (Apply)
CO4: Implement concepts and methods of Angular (Apply)
CO5: Build Dynamic web pages using server-side PHP programming with Database
Connectivity (Apply)
Course Structure:

in % Sessions
1 1. Introduction to HTML5 10 5
1.1. Basics of HTML5 – Introduction, features,
form new elements, attributes and
semantics in HTML5
1.2. <canvas>, <video>, <audio>.
1.3. Introduction to Scalable Vector Graphics
(SVG)
1.4. Introduction to Version compatibility
1.5. Installation of Apache Tomcat
(Xampp/Lampp/MySQL)
Extra Reading: Geo location, Drag, Drop, Web
Storage
2 2. Introduction to CSS3 10 5
2.1. Architecture of CSS
2.2. CSS Modules
2.3. CSS Framework
2.4. Selectors and Pseudo Classes
2.5. Fonts and Text Effects
2.6. Colors, Background Images, and Masks
Extra Reading: Transitions, Transforms and

Animations Embedding Media, Gradients, Bootstrap
3 3. Node JS 25 12
3.1. introduction and how it works
3.2. installation of node js
3.3. REPL
3.4. NPM
3.5. How modules work
3.6. Webserver Creation
3.7. Events
Extra Reading: Node.js with MySQL

4 4. Angular (Latest Stable Version) 25 12
4.1. Introduction (Features and Advantage)
4.2. Type Script
4.3. Modules
4.4. Components
4.5. Directives, Expression, Filters
4.6. Dependency Injection
4.7. Services
4.8. Routing
4.9. SPA (Single Page Application)
Extra Reading: Data binding, property binding, Event

Binding, Two-way data binding, String Interpolation.
5 5. PHP 30 11
5.1. Installing and Configuring PHP
5.2. Introduction
5.2.1. PHP and the Web Server
Architecture, PHP Capabilities
5.2.2. PHP and HTTP Environment Variables
5.2.3. Variables
5.2.4. Constants
5.2.5. Data Types
5.2.6. Operators
5.2.7. Working with Arrays
5.3. Decision Making, Flow Control and Loops
5.4. Introduction to Laravel
5.5. Creating a Dynamic HTML Form with PHP
5.6. Database Connectivity with MySQL
5.6.1. Performing basic database
operations (CRUD)
5.7. Using GET, POST, REQUEST, SESSION,
and COOKIE Variables
Extra Reading: Sending Emails, PHP with AJAX

and XML, Payment Gateway Integration
Total: 100 45
Course References:
Recommended Books:
Text Books:
1. Complete reference HTML, TMH

2. HTML5 & CSS3, Castro Elizabeth 7th Edition
3. Beginning Node.js by Basarat Ali Syed
4. Angular: Up and Running- Learning Angular, Step by Step by Shyam
Seshadri
5. Beginning PHP, Apache, MySQL web development
Reference Books
1. Introducing HTML5 - Bruce Lawson, Remy Sharp

2. Node.js in Action, 2ed by Alex Young, Bradley Meck
3. Mastering Node.js by Pasquali Sandro
4. Angular Essentials by Kumar Dhananjay
5. Complete Ref. PHP
• MOOC Courses
1) Introduction to HTML5 – University of Michigan

https://www.coursera.org/learn/html
2) Introduction to Web Development – University of California
https://www.coursera.org/learn/web-development
3) HTML, CSS and JavaScript for Web Developers – Johns Hopkins University
https://www.coursera.org/learn/html-css-javascript-for-web-developers
4) Web Design for Everybody: Basics of Web Development & Coding Specialization –
University of Michigan
https://www.coursera.org/specializations/web-design
5) Introduction to CSS3 – University of Michigan
https://www.coursera.org/learn/introcss
6) Server-side Development with NodeJS, Express and MongoDB – The Hong Kong
University of Science and Technology
https://www.coursera.org/learn/server-side-nodejs
7) Front-End Web UI Frameworks and Tools: Bootstrap 4 – The Hong Kong University
of Science and Technology
https://www.coursera.org/learn/bootstrap-4
8) Front-End JavaScript Frameworks: Angular – The Hong Kong University of Science
and Technology
https://www.coursera.org/learn/angular
9) Single Page Web Applications with AngularJS – John Hopkins University
https://www.coursera.org/learn/single-page-web-apps-with-angularjs
10) Building Web Applications in PHP – University of Michigan
https://www.coursera.org/learn/web-applications-php
11) Building Database Applications in PHP – University of Michigan
https://www.coursera.org/learn/database-applications-php
12) Web Applications for Everybody Specialization
https://www.coursera.org/specializations/web-applications
• Other Learning Material
HTML 5, CSS3, JavaScript

o https://www.htmldog.com/
o https://www.w3schools.com/
o https://qhmit.com/
o http://www.landofcode.com/
o https://www.codecademy.com/
o http://www.echoecho.com/html.htm
o https://www.awwwards.com/
Bootstrap
o https://www.w3schools.com/bootstrap4/
o https://getbootstrap.com/
o https://www.freecodecamp.org/news/learn-bootstrap-4-in-30-minute-by-building-
a-landing-page-website-guide-for-beginners-f64e03833f33/
o https://www.freecodecamp.org/news/want-to-learn-bootstrap-4-heres-our-free-
10-part-course-happy-easter-35c004dc45a4/
NodeJS
o https://nodejs.org/en/docs/guides/
o https://www.w3schools.com/nodejs/
o https://www.nodebeginner.org/
o http://visionmedia.github.io/masteringnode/
Angular
o https://www.c-sharpcorner.com/topics/angular-8
o https://www.javatpoint.com/angular-8
PHP
o https://www.php.net/manual/en/index.php
o https://phptherightway.com/
o https://www.tutorialspoint.com/php/php_useful_resources.htm
o https://www.w3schools.com/php/
1. Microsoft HTML5 and CSS3 ( https://www.microsoft.com/en-us/learning/exam-70-

480.aspx)
2. Certification available on Coursera and Udemy.
Course Code: IT-24
Course Name: Advanced DBMS
3 Hrs./Week - 3 15 10 - 50 75
Course Description:
Prerequisite:
Basics of Database Concepts
Course Objectives:
1. To understand core concepts of database management system and its types
2. To provide database design approaches using E-R model and normalization
3. To discuss transaction management and concurrency control
4. To gain an awareness of the structure of object-oriented database and its applications
5. To gain familiarization of Database crash, recovery concepts and security issues
6. To Demonstrate SQL, XML schema and NO SQL database
Course Outcomes:
CO1: Describe the core concepts of DBMS and various databases used in real applications
(Understand)
CO2: Design relational database using E-R model and normalization (Apply)
CO3: Demonstrate XML database and nonprocedural structural query languages for data
access (Apply)
CO4: Explain concepts of Parallel, Distributed and Object-Oriented Databases and their
applications (Understand)
CO5: Apply transaction management, recovery management, backup and security – privacy
concepts for database applications (Apply)
Course Structure:

in % Sessions
1 1. Introduction DBMS – Concepts & Architectures 10 4
1.1 Database and Need for DBMS, Characteristics of
DBMS
1.2 Database 3-tier schema (ANSI/SPARC) and
system architecture of DBMS
1.3 Views of data- Schemas and instances, Data
Independence
1.4 Centralized, Client-Server system, Transaction
servers, Data servers, Cloud based servers
Extra Reading: Indexing and Hashing - Basic concepts of

indexing, ordered index, B+ tree index, B+ tree
extensions, Multiple key access, Hashing concepts, types
of hashing, Bitmap indices
2 2. Data Modelling and Relational Database Design 16 8
2.1 Data Modelling using ER Diagram: Representation
of Entities, Attributes, Relationships and their
Type, Cardinality, Generalization, Specialization,
Aggregation.
2.2 Relational data model: Structure of Relational
Database Model, Types of keys, Referential
Integrity Constraints
2.3 Codd’s rules
2.4 Database Design using E-R, E-R to Relational
2.5 Normalization – Normal forms based on primary
(1 NF, 2 NF, 3NF, BCNF)
Note: Case studies based on E-R diagram &

Normalization
Extra Reading: Database languages - Relational Algebra,

Relational database languages, Data definition in SQL,
Views and Queries in SQL, Joins, specifying constraints
and Indexes in SQL, Specifying constraints management
systems Postgres/ SQL/MySQL
3 3. Transaction and Concurrency control 13 6
3.1. Concept of transaction, ACID properties, States
of transaction
3.2. Concurrency control, Problems in concurrency
controls
3.3. Scheduling of transactions, Serializability and
testing of serilaizibity
3.4. Lock-based Protocol and Time stamp-based
ordering protocols
3.5. Deadlock Handling
Extra Readings: Semantic data controls & Multi-version

concurrency control
4 4. Parallel Databases 13 6
4.1. Introduction to Parallel Databases
4.2. Parallel Database Architectures
4.3. I/O parallelism
4.4. Inter-query and Intra-query parallelism
4.5. Inter-operational and Intra-operational
parallelism
4.6. Key elements of parallel database processing:
Speed-up, Scale-up Synchronization and Locking
Extra Readings: Parallel handling and Load balancing

5 5. Distributed Databases 13 6
5.1. Introduction to Distributed Database System
5.2. Homogeneous and Heterogeneous Databases
5.3. Distributed data storage (Fragmentation and
Replication)
5.4. Distributed transactions
5.5. Concurrency control schemes in DDBMS
5.6. Commit protocols 2 phase and 3 Phase Commit
Protocol
Extra Readings: Reliability issues in DDBMS and Web

based interface of DDBMS
6 6. Object Oriented Databases & Applications 10 4
6.1. Overview of Object- Oriented Database concepts
& characteristics
6.2. Database design for OODBMS – Objects, OIDs
and reference type
6.3. Spatial data and Spatial indexing (Any two
techniques)
6.4. Mobile Database: Need, Structure, Features,
Limitations and Applications
6.5. Temporal databases, temporal aspects valid
time, transaction time or decision time
6.6. Multimedia Database: Architecture, Type and
Characteristics
7 7. Crash Recovery and Backup 10 5
7.1. Failure classifications
7.2. Recovery & Atomicity
7.3. Log based recovery
7.4. Checkpoint and Shadow Paging in Data recovery
7.5. Database backup and types of backups
Extra Readings: Role and Functions of Database

administrator
8 8. Security and Privacy 10 4
8.1. Database security issues
8.2. Discretionary access control based on grant &
revoking privilege
8.3. Mandatory access control and role-based access
control for multilevel security
8.4. Encryption & public key infrastructures
9 9. NO-SQL Database 5 2
Introduction, Types of NOSQL, Need of NoSQL
databases, Use Cases
Total: 100 45
1. To install and configure database software (ORACLE/MYSQL)

2. To design a database (logical & physical database)
3. To Perform all SQL operations and queries on designed physical database
4. To install and configure NO-SQL database and practice for core operations
5. To perform experiments on database crash and recovery
6. To perform experiments on database Backup – restoring operations on database server
7. To perform some operations on Object oriented databases
Course References:
Recommended Books:
Text Books:
1.
2. Introduction to database systems C.J. Date, Pearson.
3. Fundamentals of Database Systems by Elmasri Navathe
4. Principles of Database Management James Martin, PHI
5. Database System Concepts by Abraham Silberschatz, H. Korth, Sudarshan
Reference Books:
1. Database Management System by Raghu Ramakrishnan / Johannes Gherke

2. Database Management System (DBMS)A Practical Approach. By Rajiv Chopra
3. Database system practical approach to design, implementation & management
by Connoly & Begg,
4. NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence
Martin Fowler
1. Oracle certified associate (OCA)

2. Oracle certified professional (OCP)
3. Database administrator (DBA)
4. Database related certification courses available at NPTEL/Coursera/Udemy
Course Code: IT-21L
- 10 Hrs./Week 5 - 75 - 50 125
Course Description:
1. List of Practicals – Python Programming

2. List of Practicals – Advanced Internet Technologies
Course Outcomes:
CO1: implement python programming concepts for solving real life problems. (Apply)
CO2: Implement Advanced Internet Technologies (Apply)
Course Structure:
List of Practicals – Python Programming
Note:
• Recommended IDE for python – IDLE
• Exception handling concepts should be used with file handling programs.
1. Python installation and configuration with windows and Linux

2. Programs for understanding the data types, control flow statements, blocks and loops
3. Programs for understanding functions, use of built in functions, user defined functions
4. Programs to use existing modules, packages and creating modules, packages
5. Programs for implementations of all object-oriented concepts like class, method, inheritance,
polymorphism etc. (Real life examples must be covered for the implementation of object-
oriented concepts)
6. Programs for parsing of data, validations like Password, email, URL, etc.
7. Programs for Pattern finding should be covered.
8. Programs covering all the aspects of Exception handling, user defined exception, Multithreading
should be covered.
9. Programs demonstrating the IO operations like reading from file, writing into file from different
file types like data file, binary file, etc.
10. Programs to perform searching, adding, updating the content from the file.
11. Program for performing CRUD operation with MongoDB and Python
12. Basic programs with NumPy as Array, Searching and Sorting, date & time and String handling
13. Programs for series and data frames should be covered.
14. Programs to demonstrate data pre-processing and data handling with data frame
15. Program for data visualization should be covered.
List of Practicals – Advanced Internet Technologies
1. Program to implement Audio and Video features for your web page.
2. Program to design form using HTML5 elements, attributes and Semantics.
3. Programs using Canvas and SVG.
4. Programs to demonstrate external and internal styles in the web page using font, text,
background, borders, opacity and other CSS 3 properties.
5. Implement Transformation using Translation, Rotation and Scaling in your web page.
6. Program to show current date and time using user defined module
7. Program using built-in modules to split the query string into readable parts.
8. Program using NPM which will convert entered string into either case
9. Write a program to create a calculator using Node JS. (Install and configure Node JS and Server)
10. Write Program for Form validation in Angular.
11. Program to demonstrate the ngif, ngfor, ngswitch statements.
12. Create angular project which will demonstrate the usage of component directive, structural
directive and attribute directives
13. Create angular project which has HTML template and handle the click event on click of the
button (Installation of Angular and Bootstrap 4 CSS Framework)
14. Program for basic operations, array and user interface handling.
15. Program to demonstrate session management using various techniques.
16. Program to perform the CRUD Operations using PHP Script.
Course Code: ITC21
- 10 Hrs./Week 5 - 75 - 50 125
Course Description:
A mini project is an assignment that the student needs to complete at the end of every semester to
strengthen the understanding of fundamentals through effective application of the subjects learnt.
Course Outcomes:
CO1: Create working project using tools and techniques learnt in this semester (Create)
Course Structure:
1. Students are expected to undertake one mini project starting from first semester till third
semester.
2. The student may take up the mini project in first semester based on the courses learnt in that
semester and for every next semester the mini project may be based on the courses learnt in
the current semester along with all the subjects learnt in earlier semesters.
3. The student may take up the project individually or in group. However, if project is done in
group, each student must be given a responsibility for distinct modules.
4. Selected project/module must have relevant scope as per the marks assigned and must be
carried out in the Institute.
5. Internal guide should monitor and evaluate the progress of the project on individual basis
through handwritten workbook (Project Diary) maintained by students containing various
project milestones with learnings and remarks from internal guide for concurrent evaluation.
6. The Project Synopsis should contain an Introduction to Project clearly stating the project scope
in detail justifying enough scope for 125 marks. The project work will carry 75 marks for internal
assessment and 50 marks for external assessment.
8. Students are expected to upload mini-project on GITHUB as project repository of the
institution.
submission.
10. The project will be assessed internally as well as externally by the examiners appointed by
University. University may appoint Industry Experts as an external examiner
11.
Savitribai Phule Pune University, Pune
Faculty of Commerce and Management
Master of Computer Applications (MCA)
Programme Curriculum ( Sem. III & IV)

(2020-2022)
Semester III
Course Code: IT-31
Course Name: Mobile Application Development
3 Hrs./Week - 3 25 - - 50 75
Course Description:
Course Objectives:
1. To understand the different mobile application Architectures.
2. To understand different types of widgets like buttons, views, layout etc.
3. To know the ways of application handling like intents, adapters, Notifications,
Web Services and Web View.
4. To learn and know about data storing, retrieval and sharing in android.
5. To explore cross platform mobile application development framework, React
Native and Flutter.
Course Outcomes:
CO1: Understand Various Mobile Application Architectures. (Understand)
CO2: Apply different types of widgets and Layouts. (Apply)
CO3: Describe Web Services and Web Views in mobile applications. (Understand)
CO4: Implement data storing and retrieval methods in android. (Apply)
CO5: Demonstrate Hybrid Mobile App Framework. (Apply)
Course Structure:
No. in % Sessions
1 1. Mobile application development architectures 14 5
1.1. Introduction to Mobile Application technologies
1.2. Android Architecture
1.3. IOS Architecture
1.4. Windows Architecture
1.5. Hybrid Architecture
2 2. Creating Android Application 20 10
2.1. Creating Android project
2.2. Project Structure
2.3. Activity and Activity Life Cycle
2.4. Fragment and Fragment Life Cycle
2.5 Views and View groups
3 3. Interactivity Tools 20 10
3.1. Intents and Filters
3.2. Adapters
3.3. Dialogs
3.4. Menus
3.5. Notifications
4 4. Interaction with Database 16 6

4.1. Introduction to Database (SQLite and Firebase)
4.2. Cursors and content values
4.3. CURD Operations
5 5. Web Services and Web View 12 5
5.1. Introduction to web services
5.2. Receiving HTTP Response (JSON, XML)
5.3. Parsing JSON and XML
5.4. Introduction to Web View
6 6. React Native 10 5
6.1. Introduction
6.2. Environment Setup
6.3. JavaScript ES6 Overview
6.4. Create React Native App
6.5. React Native Alert API
6.6. React Native Geolocation API
6.7. Third Party Libraries
7 7. Introduction Flutter 8 4
7.1. Overview of Flutter
7.2. Installation of Flutter
7.3. Architecture of Flutter
7.4. Introduction to Dart Programming
7.5. Demonstration of Simple application
Total: 100 45
Course References:
Reference Books:
1. Professional Android 4 Application Development by Meier, Reto -

Wiley Education
2. Beginning Android 4 Application Development by Lee, Wei- Meng -
Wiley Education
3. Android application Development: in 24 hours by Delessio, Carmen;
Darcey, Lauren; Conder, Shane - Pearson Education
4. Android by Dixit, Prasanna Kumar - Vikas Publishing House
5. Android Studio Development Essentials Book by Neil Smith
6. Beginning App Development with Flutter by Rap Payne
7. Flutter in Action by Eric Windmill
8. REACT NATIVE IN ACTION DEVELOPING IOS AND ANDROID APPS
WITH JAVASCRIPT BOOK BY NADER DABIT
Web Reference:
1. https://developer.android.com
2. https://facebook.github.io/react-native/docs/tutorial
3. https://flutter.dev/docs/get-started/install
Course Code: IT-32
Course Name: Data Warehousing and Data Mining
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Course Objectives:
1. To introduce the concepts, techniques and applications of data warehousing and
data mining.
2. To understand how to Preprocess, understand and analyze various kinds of data
3. To Study data warehouse Concepts, architectures, OLAP and the project planning
aspects in building a data warehouse
4. To enable students to understand and implement various techniques of association,
classification and clustering in data mining
5. To enable students to understand and implement the concepts of Web mining and
Text Mining in data mining
Course Outcomes:
CO1: Understand Data warehouse concepts, architecture and models (Understand)
CO2: Learn and understand techniques of preprocessing on various kinds of data
(Understand)
CO3: Apply association Mining and Classification Techniques on Data Sets (Apply)
CO4: Apply Clustering Techniques and Web Mining on Data Sets (Apply)
CO5: Understand other approaches of Data mining (Understand)
Course Structure:

No. in % Sessions
1 1. Data Warehouse Fundamentals
1.1. Introduction to Data Warehouse, OLTP Systems;
Differences between OLTP Systems and Data
15
Warehouse: 6
1.2. Characteristics of Data Warehouse; Functionality of
Data Warehouse:
1.3. Advantages and Applications of Data Warehouse;
Top- Down and Bottom-Up Development
Methodology:
1.4. Tools for Data warehouse development: Data
Warehouse Types
1.5. Planning and Project Management in constructing
Data warehouse: Data Warehouse Project;
1.6. Data Warehouse development Life Cycle, Kimball
Lifecycle Diagram
2 2. Data Warehouse Architecture
2.1. Introductions, Components of Data warehouse
Architecture
2.2. Technical Architectures; Federated Data Warehouse 15 6
Architecture: Tool selection;
2.3. Dimensional Modeling: E-R Modeling VS
Dimensional Modeling
2.4. Data Warehouse Schemas; Star Schema, Inside
Dimensional Table, Inside Fact Table, Fact Less Fact
Table, Granularity, Star Schema Keys: Snowflake
Schema, Fact Constellation Schema
2.5. Introduction to Metadata : Categorizing Metadata:
2.6. Metadata management in practice; Meta data
requirements gathering, Metadata classification,
Meta data collection strategies, Tools for Metadata
Management
3 3. Data Preprocessing and ETL

3.1. Data Pre-processing: Data Cleaning tasks
3.2. Data Integration and Data Reduction
3.3. Discretization and Concept Hierarchy Generation
3.4. Data Transformation; Basic Tasks in Transformation,
20 7
Major Data Transformation Types
3.5. Introduction to ETL(Extract, Transform and Load)
3.6. ETL requirements and steps: Data Extraction;
Extraction Methods, Logical Extraction Methods,
Physical Extraction Methods
3.7. Data loading; Data Loading Techniques, ETL Tools
4 4. Data Warehouse & OLAP: 10 5
4.1. Introduction: What is OLAP?; Characteristics of
OLAP,
4.2. Steps in the OLAP Creation Process, OLAP
operations, Advantages of OLAP: Multidimensional
Data:
4.3. OLAP Architectures; MOLAP, ROLAP, HOLAP:
4.4. Data Warehouse and OLAP: Hypercube &
Multicubes
5 5. Introduction to Data Mining:
5.1. Introduction and Scope of Data Mining
5 4
5.2. How does Data Mining Works, Predictive Modeling
5.3. Data Mining and Data Warehousing
5.4. Architecture for Data Mining
5.5. Profitable Applications: Data Mining Tools:
6 6. Data Mining Techniques

6.1. An Overview: Introduction, Data Mining, Data
15 6
Mining Versus Database Management System,
6.2. Data Mining Techniques- Association rules( Apriori,
FP Tree algorithms)
6.3. Classification (Decision Tree induction, Bayesian
classification, SVM, KNN)
6.4. Clustering, Neural networks.
6.5. Evaluating Association rules , Classification model
7 7. Clustering
7.1. Introduction to Clustering, Cluster Analysis
10 5
7.2. Clustering Methods- K means, Hierarchical
clustering, Agglomerative clustering, Divisive
clustering,
7.3. clustering and segmentation software
7.4. Evaluating clusters
7.5. Data Mining trends and Applications
8 8. Web Mining
8.1. Introduction, Terminologies
10 6
8.2. Categories of Web Mining: Web Content Mining,
Web Structure Mining, Web Usage Mining
8.3. Applications of Web Mining, and Agent based and
Database approaches, Web mining Software/Tools.
8.4. Text Mining: process and types, steps in Text
Mining, applications and tools of Text Mining
8.5. Data visualization, Dashboard- KPI, Business
Intelligence and its future.
Total: 100 45

1. Creating a simple data warehouse & performing OLAP operations using simple tools
2. Extracting data from any Operational database (ETL) and performing pre-processing
tasks
3. Performing association mining on large data sets and extracting best possible rules / a
case study
4. Performing classification and evaluating the efficient model / a case study
5. A case study on finding efficient Clusters on very large set of documents data
6. A case study on Web mining and Text mining using software tools
Students may practice or implement Data warehouse, ETL & Data mining concepts on the
following software/ tools (Students versions) at on premise / Cloud based platform
1) Data warehouse - My-SQL, MongoDB / Google BigQuery / Amazon Redshift / Talend
2) ETL Tools : Pentaho Kettle / Talend-Open Studio / Apache Kafka / Informatica Power
Center
3) BI and Analytics tools : Python / XL-Miner, R-Studio / Rapid-Miner Studio
4) Visualization Tools : Tableau / Power-BI / Qlick sense
Course References:
Recommended Books:
Text Books:
1. Data Mining: Introductory and Advanced Topics, by Margaret

Dunham, Pearson Education
2. Data Mining by Arun K. Pujari – University Press.
Reference Books:
1. DATAWAREHOUSING FUNDAMENTALS: A COMPREHENSIVE GUIDE

FOR IT PROFESSIONALS, by Paulraj Poonniah, Latest Edition
2. Building the Data Warehouse, 3rd edition by W. H. Inmon
3. Data Mining concepts and Techniques by Jiawei Han, Micheline
Kambler –Elsevier.
4. Data Mining practical Machine Learning Tools and Techniques by Ian
H. Witten Eibe Frank Mark Hall - Elsevier publication
5. Introduction to Data Mining with Case Studies by G. K. Gupta, Prentice
Hall
Web Reference:
1. www.ibm.com/in/en/
2. www.pentaho.com/
3. www.jaspersoft.com/
4. www.amazon.com/Data-Mining-Business-Intelligence-Applications
5. www.ibm.com/insights/in
6. www.sas.com
7. Weka– Data Mining with Open Source Machine Learning Software,
www.cs.waikato.ac.nz/ml/weka.
8. https://cloud.google.com/bigquery/
9. https://www.rstudio.com/ 10.https://aws.amazon.com/redshift/
Course Code: IT-33
Course Name: Software Testing and Quality Assurance
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Course Objectives:
1. To understand the principles of software development emphasizing
processes and activities of quality assurance
2. To study fundamental concepts in software testing, including software testing
objectives, process, strategies and methods.
3. To understand test design techniques based on functionality and structure of
software
4. To understand test planning, monitoring and control process
5. To gain the techniques and skills on how to use software testing tools to
support software testing activities
Course Outcomes:
CO1: Understand the role of software quality assurance in contributing to the
efficient
delivery of software solutions. (Understand)
CO2: Demonstrate specific software tests with well-defined objectives and
targets. (Apply)
CO3: Apply the software testing techniques in commercial environments. (Apply)
CO4: Construct test strategies and plans for software testing. (Analyze)
CO5: Demonstrate the usage of software testing tools for test effectiveness,
efficiency and
coverage (Apply)
Course Structure:

No. in % Sessions
1 1. Software Quality Assurance Fundamentals 20 6
1.1. Definition of Quality, Quality Assurance, Quality
Control, Difference between QA and QC, Software
Quality Assurance Challenges
1.2. Software Quality Assurance, SQA Planning &
Standards (ISO 9000, Six Sigma)
1.3. SQA Activities
1.4. Building Blocks of SQA
1.5. Software Quality factors
1.6. Software Quality Metrics: Process Metrics &
Product Metrics
1.7. Software Reliability & Reliability Measurement
Factors: ROCOF, MTTF, MTTR, MTBF, POFOD,
Availability
Extra Reading:
ISO/IEC 9126, ISO/IEC 25010:2011, Malcom Balridge
2 2. Software Testing Fundamentals 17 10
2.1. Definition & Objectives of Testing
2.2. Role of testing and its effect on quality
2.3. Causes of software failure: Definition of -Error, Bug,
Fault, Defect and Failure,
2.4. Economics of Testing
2.5. Seven Testing Principles
2.6. Software Testing Life cycle
2.7. Validation & Verification Concepts - V Model and W
Model
2.8. Agile Testing- Test Driven Software Development
2.9. Levels of Testing-
2.9.1. Unit (Component) Testing
2.9.2. Integration Testing
2.9.3. System Testing
2.9.4. User Acceptance Testing (UAT)
2.10. Test Types
2.10.1. Functional testing (Black-box)
2.10.2. Non-functional testing (Testing of software
product characteristics)
2.10.3. Structural testing (White-box)
2.10.4. Testing related to changes - Confirmation
(Re-testing) and Regression Testing
2.11. Non-Functional Testing Types –
2.11.1. Performance (Load & Stress)
2.11.2. Usability
2.11.3. Maintainability
2.11.4. Portability
2.11.5. Security
2.11.6. Localization & Internationalization
2.12. Concept of Smoke testing and Sanity Testing
3 3. Static Testing 8 3
3.1. Static Techniques – Review
3.1.1. Review Process (Informal & Formal)
3.1.2. Desk Checking,
3.1.3. Technical or Peer Review
3.1.4. Walkthrough
3.1.5. Inspection
3.2. Static Techniques – Static Analysis
3.2.1. Data flow analysis
3.2.2. Control flow analysis,
3.2.3. Static Analysis by Tools (Automated Static
Analysis)
Case Study on Preparation of Inspection Checklist

4 4. Dynamic Testing 15 7
4.1. Test Design Techniques-Black Box Testing
Techniques:
4.1.1. Equivalence Partitioning
4.1.2. Boundary Value Analysis
4.1.3. Decision Table Testing
4.1.4. State Transition Testing
4.2. Test Design Techniques -White Box Testing
Techniques (coverage based and fault-based)
4.2.1. Statement coverage
4.2.2. Branch & Decision coverage
4.2.3. Path coverage
4.2.4. McCabe’s Cyclomatic Complexity Metric
(Computation of Cyclomatic Complexity to be
covered)
4.2.5. Data Flow based Testing
4.2.6. Mutation Testing
4.3. Test Design Techniques -Experience based
techniques:
4.3.1. Error Guessing
4.3.2. Exploratory Testing
Problems based on Black Box and White Box Testing

Techniques to be covered
5 5. Test Management 25 10
5.1. Test Organization- Roles & Skills of Tester, Test
Lead, Test Manager
5.2. Test Planning- Test Plan as per IEEE 829 STANDARD
TEST PLAN TEMPLATE
5.3. Test Process Monitoring & Control
5.3.1. Test Monitoring through -Test Log (IEEE 829:
TEST LOG TEMPLATE to be discussed) and
Defect Density
5.3.2. Reporting Test Status (IEEE 829: TEST
SUMMARY REPORT TEMPLATE to be discussed)
5.3.3. Test Control
5.4. Requirement Traceability Matrix (Horizontal &
Vertical), Test Scenario, Test Suite, Test Cases (both
Positive & Negative Test Cases, as per IEEE 829:
TEST CASE SPECIFICATION TEMPLATE)
5.5. Configuration Management- Configuration
Management support for Testing
5.6. Risk and Testing- Project Risk & Product Risk
5.7. Incident/ Defect Management
5.7.1. Defect Life Cycle
5.7.2. Defect/ Incident Report (IEEE 829: TEST
INCIDENT REPORT TEMPLATE to be discussed)
Case Study on Test Plan for applications and Case study on

Test Cases for different features within applications
Extra Reading: Version Control Tool: SVN, Defect Tracking

Tool: Bugzilla, JIRA
6 6. Tool Support for Testing 15 9
6.1. Types of Test tools –CAST (only type & their
purpose should be covered)
6.2. Effective Use of Tools: Potential Benefits and Risks
6.3. Introduction of a tool into an organization
6.4. Testing tools
6.4.1. Selenium -WebDriver and Test NG
6.4.2. Appium
6.4.3. JMeter
Extra Reading: Functional Test Automation Tools: Quick

Test Professional (QTP), IBM Rational Robot, Non-functional
Test Automation Tools: Load Runner, Test Management
Tools: Test Director, Test Link, Bugzilla, Redmine, API
Testing Tool: Postman, ETL Testing Tool, Big Data Testing
Tool, AI based Testing Tool: Test Craft, UI Testing, Website
Testing: TestRail
Total: 100 45
Practicals based on Selenium
1. Focusses on how to invoke the Firefox browser, maximizing the window,

navigate commands, etc.
Scenario:
1.1. Open the Firefox browser.
1.2. Maximize the browser window.
1.3. Navigate to a particular URL (let say, SPPU website)
“http://www.unipune.ac.in/”.
1.4. Write a method to print PASS if the title of the page matches with the page
title else FAIL. (If you are familiar with TestNG or JUnit use assert statement
like assert.assertequals(actual, expected) to give a verdict of the pass or fail
status.
1.5. Navigate to another URL (let say, the Facebook page)
“https://www.facebook.com”
1.6. Navigate back to the QA Tech Hub website.
1.7. Print the URL of the current page.
1.8. Navigate forward.
1.9. Reload the page.
1.10. Close the Browser.
2. Focusses on interacting with form elements like textbox, buttons, radio buttons
and drop-down (Facebook Signup)
Scenario:
2.1. Open a browser.
2.2. Navigate to “http://www.fb.com”
2.3. Verify that the page is redirected to “http://www.facebook.com”, by getting
the current URL. (use if-else condition to verify this condition or use
Assert.assertequals() in case you are familiar with TestNG or JUnit)
2.4. Verify that there is a “Create an account” section on the page.
2.5. Fill in the text boxes: First Name, Surname, Mobile Number or email address,
“Re-enter mobile number”, new password.
2.6. Update the date of birth in the drop-down.
2.7. Select gender.
2.8. Click on “Create an account”.
2.9. Verify that the account is created successfully.
3. Focusses on working with links and getAttribute() method.

Scenario:
3.1. Open a Browser (write the generic code such that by changing the
parameter browser can be changed.)
3.2. Navigate to https://flipkart.com website.
3.3. Write a method to find the count (number of) links on the homepage of
Flipkart.
3.4. Write another method to print link text and URLs of all the links on the page
of Flipkart.
4. Focusses on Frame Handling, mouse over operations (Login to an application)

Scenario:
4.1. Open any browser of your choice, for example, Chrome Browser.
4.2. Navigate to Snapdeal site (http://www.snapdeal.com)
4.3. Move to Sign in Button and hold
4.4. Move to the Sign In button and click.
4.5. Enter valid Email Id and click continue.
4.6. Enter the valid password and click LOGIN.
4.7. Verify that the user is logged in successfully.
5. Focusses on writing dynamic xpath (Login to Gmail Account and sending a mail
from Gmail)
Scenario:
5.1. Open any browser of your choice, say Mozilla Firefox
5.2. Navigate to https://www.gmail.com
5.3. Enter a valid Email Id or Phone Number
5.4. Click Next button
5.5. Enter Password and click “Sign in” button.
5.6. Verify that Gmail is logged in successfully.
5.7. Click compose button and verify that a new mail window is opened.
5.8. Enter an Email Id
5.9. Enter some subject, say “Test Mail”
5.10. Enter some text in body
5.11. Click send button.
Course References:
Recommended Books:
Text Books:
1. Foundations of Software Testing by Rex black, Erik Van Veenendaal,

Dorothy Graham (2012)-Cengage Learning: London UK, 3rd Edition
2. Software Engineering by Sommerville-Pearson,8thEdition
3. Daniel Galin, “Software Quality Assurance: From Theory to
Implementation”, Pearson Addison-Wesley, 2012. 2.
4. Effective Methods for Software Testing by William Perry- Wiley Pub,
3rd Edition.
Reference Books:
1. Roger S. Pressman, “Software Engineering-A Practitioner’s Approach”,

McGraw Hill pub.2010
2. Software Testing in Real World Edward Kit- Pearson Pub
3. Software Testing Techniques by Boris Beizer-DreamTech Pub,2nd
Edition
4. Software Testing by Ron Patton, TechMedia Pub.
5. Introducing Software by Testing Louise Tamres
6. Fundamentals of Software Engineering –Rajib Mall, 3rd Edition
7. Allen Gilles “Software quality: Theory and management”,
International Thomson, Computer press 1997.
8. Software Testing Principles Techniques and Tools by Milind. G.
Limaye- Tata McGraw Hill Pub.
9. Stephen H. Kan, “Metrics and models in software quality
Engineering”, Addison –Wesley 2003.
Web Reference:
1. www.istqb.org
2. https://www.seleniumhq.org/
3. https://www.softwaretestingmaterial.com/selenium-tutorial/
4. https://www.toolsqa.com/selenium-tutorial/
5. www.guru99.com/software-testing.html
6. www.guru99.com/selenium-tutorial.html
7. www.guru99.com/mobile-testing.html
8. https://www.softwaretestinghelp.com/appium-tutorial-for-
beginners/
9. www.professionalqa.com
10. www.resources.sei.cmu.edu/library
11. www.iist.org
Course Code: IT-34
Course Name: Knowledge Representation and Artificial
Intelligence: ML, DL
3 Hrs./Week - 3 25 -- -- 50 75
Course Description:
Course Objectives:
Course Outcomes:
CO1: Understand basic building block of Artificial Intelligence and Knowledge
Representation.
(Understand)
CO2: Apply Propositional Logic for knowledge representation. (Apply)
CO3: Design various models based on Machine Learning methodology (Apply)
CO4: Design various models based on Deep Learning methodology (Apply)
CO5: Understand various hardware and software aspect used for AI and its
application.
(Understand)
Course Structure:

No. in % Sessions
1 1. Artificial Intelligence and Knowledge representation 15 3
1.1. Introduction to Artificial Intelligence and its
evolution.
1.2. What is Intelligence and Artificial Intelligence
1.3. How AI is affecting on real life?
1.4. Different branches of AI
1.5. Limitations of AI
1.6. Need of knowledge Representation
1.7. Knowledge Representation and Mapping schemes
1.8. Properties of good knowledge-based system
1.9. Types of knowledge
1.10. Knowledge Representation issues
1.11. AND-OR Graph
1.12. The Wumpus World
2 2. Propositional Logic 15 8
2.1. Mathematical Logic and Inference
2.2. First Order Logic: Syntax and Semantic, Inference in
FOL
2.3. Forward chaining, backward Chaining
2.4. Language
2.5. Semantics and Reasoning
2.6. Syntax and Truth Values,
2.7. Valid Arguments and Proof Systems
2.8. Rules of Inference and Natural Deduction
2.9. Axiomatic Systems and Hilbert Style Proofs
2.10. The Tableau Method
2.11. The Resolution Refutation Method
Problems based on FOPL

3 3. Machine Learning 30 15
3.1. History of Machine Learning
3.2. Machine Learning Vs Statistical Learning
3.3. 3Type of Machine Learning - Supervised,
Unsupervised Learning, Reinforcement Learning
3.3.1. Linear Regression
3.3.2. Logistic Regression
3.3.3. Support Vector Machines
3.3.4. Random Forest
3.3.5. Naïve Bayes Classification
3.3.6. Ordinary Least Square Regression
3.3.7. K-means
3.4. Essentials of Data and its analysis
3.5. Framework of Data Analysis
Extra Reading: Forms of Learning, Inductive Learning,

Ensemble Methods, Apriori Algorithm, Principal Component
Analysis, Singular Value Decomposition, Reinforcement or
Semi-Supervised Machine Learning, Independent
Component Analysis
4 4. Deep Learning 30 15
4.1. Fundamentals of Deep networks and Defining Deep
learning
4.2. Deep learning Problem types
4.2.1. ANN
4.2.2. CNN
4.2.3. RNN
4.2.4. GAN
4.2.5. NLP
4.3. Building blocks of Deep learning
4.4. Classification and Detection
Algorithms should be taught using Python Library –
Pytorch
Extra Reading: DNN, Transfer Learning, Architectural

Principals of Deep networks – AlexNet, VGG 16, Inception,
MobileNet
5 5. Hardware and Software for AI 5 2
5.1. Data Center
5.2. Gateway edge computing
5.3. Keyprocessor for AI
5.4. CPU and GPU
5.5. Field Programmable Gate Array (FPGA)
6 6. Application of AI 5 2
6.1. Robotics Process Automation – Chatbot
6.2. NLP
6.3. Image Processing
6.4. Speech Recognition
Total: 100 45
Course References:
Recommended Books:
Reference Books:
1. Artificial Intelligence, 3rd Edition, Elaine Rich, Kevin Knight, S.B.
Nair - Tata McGraw Hill.
2. Artificial Intelligence: A Modern Approach Textbook by Peter
Norvig and Stuart J. Russell
3. Artificial Intelligence by Patrick Henry Winston - Addison-
Wesley, Third Edition.
4. Artificial Intelligence and Intelligent Systems by N.P.Padhy -
Oxford University Press.
5. Data Mining practical Machine Learning Tools and Techniques by
Ian H. Witten Eibe Frank Mark Hall - Elsevier publication
6. Python Machine Learning and Deep Learning with Python Scikit-
learn, and TensorFlow 2, 3rd Edition by Sebastian Raschka, Vahid
Mirjalil
7. Machine Learning by Tom M Mitchell – TMGH Publication
8. Machine Learning using Python by Manaranjan Pradhan and U.
Dinesh Kumar – WILEY Publication
9. Machine Learning for Big Data – Hands on for Developers and
Technical Professionals by Jason Bell – WILEY Publication
Course Code: IT-35
Course Name: Cloud Computing
3 Hrs./Week - 3 10 10 5 50 75
Course Description:
Course Objectives:
1. To introduce the fundamentals of cloud computing, its technologies, Challenges

and Applications
2. To give Insights into the virtualization technologies and Architecture
3. To know the relationship between Cloud and SOA
4. To classify and evaluate Cloud Security Issues
5. To apply theory to practical knowledge through case Studies
Course Outcomes:
CO1: Describe the concepts of Cloud Computing and its Service Models&
Deployment Models.
(Understand)
CO2: Classify the types of Virtualization. (Understand)
CO3: Describe the Cloud Management and relate Cloud to SOA. (Understand)
CO4: Interpret Architecture and Pharrell Programing of Cloud Computing. (Apply)
CO5: Demonstrate practical implementation of Cloud computing. (Apply)
Course Structure:

No. in % Sessions
1 1. Cloud Services and Cloud Models 20 7
1.1. Introduction to Cloud
1.2. Cloud Computing vs. Cluster Computing vs. Grid
Computing
1.3. Introduction to Cloud Service Models
1.4. Characteristics, Advantages, Security
1.5. XAAS- Anything as a Service – Storage as a service,
Network as a Service, Database as a Service etc.
1.6. IAAS, PAAS, SAAS characteristics, benefits and
Applications
1.7. Comparison of SAAS, PASS and IAAS
1.8. Cloud Deployment Models-Public, Private, Hybrid
1.9. Cloud Platforms :
1.9.1. Google Cloud Platform,
1.9.2. Microsoft Azure
1.9.3. SalesForce,
1.9.4. AWS.
Extra Reading: Offerings of AWS

2 2. Virtualization 15 8
2.1. Introduction to Virtualization concept &Hypervisors
2.2. Types of Virtualization: Server, Storage and Network
2.3. Pros and Cons of Virtualization
2.4. Machine Image, Virtual Machine (VM)
2.5. Technology Examples
2.5.1. Xen: Para virtualization
2.5.2. VMware: Full Virtualization
2.5.3. Open Source Virtualization Manager
3 3. SOA & Cloud Management 15 8

3.1. Definition of Service Oriented Architecture
3.2. Basic concepts of SOA
3.3. Web Services: SOAP and REST
3.4. Cloud APIs (RESTful)
3.5. Relating SOA and Cloud Computing.
3.6. Cloud Availability
3.7. Cloud Governance
3.8. Service Level Agreement
Extra Reading: Pricing Model: Usage Reporting, billing and

metering (AWS), Cloud Statistics
4 4. Multi Core Architecture 15 6
4.1. Cloud Computing Architecture
4.2. Multi Core Architecture
4.3. Multi Cloud Environment
4.4. Parallel Programming
4.5. Parallel Processing
4.6. Edge Computing Concepts
5 5. Moving Applications to the Cloud 15 6
5.1. Cloud Migration Strategies and Process
5.2. Issues in Inter Cloud
5.3. Applications in the Clouds
5.4. Cloud Service Attributes
5.5. Cloud Bursting.
5.6. Data Migration in Cloud
5.7. 5Quality of Services in cloud Computing
Extra Reading: Six R for Cloud Migration

6 6. Cloud Security & Implementation of Cloud 20 10
6.1. Cloud Security Fundamentals
6.2. Cloud Security Architecture
6.3. Cloud Computing Security Challenges
6.4. Privacy and Security in Cloud
6.5. Identity Management and Access control
6.6. Demonstrate the commercial cloud computing
Infrastructures
6.7. Introduction to Dockers Container
6.8. Case Study’s based on Cloud Computing Concepts.
Total: 100 45

1. Create an Account to Cloud Service Provider (AWS, AZURE, Google Cloud, etc.)
2. Create an Instance on Cloud
3. Provide Access Control and Permission to Users
4. Execute the Web Page on Cloud
5. Provide Security Mechanism to your instance.
Course References:
Recommended Books:
Reference Books:
1. Cloud Computing Bible by Barrie Sosinsky, Wiley India Pvt. Ltd,

2. Cloud Computing : Automating the Virtualized Data Center
3. Cloud Computing by Dr. Kumar Saurabh ,Wiley–India
4. Cloud computing: A practical approach by Anthony T. Velte, Tata
McGraw-Hill
5. Cloud Computing Concepts, Technology & Architecture by Thomas Erl,
Zaigham Mahmood, and Ricardo Puttin
6. Mastering Cloud Computing by Rajkumar Buyya, Christian Vecchiola,
S.Thamarai Selvi - McGraw Hill Education (India) Private Limited,
7. Cloud Computing Web –Based Applications that change the way you
work and Collaborate Online by Michael Miller, Pearson
8. Cloud Computing for Dummies by Judith Hurwitz, Robin Bloor, Marcia
Kaufman, FernHalper
Web Reference:
1. http://www.cloudcomputingpatterns.org/
2. http://whatiscloud.com
3. www.w3schools.com
Course Code: IT-31L
- 10 Hrs./Week 5 - 75 - 50 125
Course Description:
1. List of Practicals – Mobile Application Development

2. List of Practicals – KR an AI, ML, DL
Course Outcomes:
CO1: Develop mobile application. (Apply)

CO2: Develop ML, DL models using Python (Apply)
Course Structure:
Suggestive List of Practicals
Mobile Application Development
1. Demonstrate different Layouts with different views in android Layouts-

ConstraintLayout, RelativeLayout, TableLayout Views- Button, TextView,
EditText, WebView, CheckBox, RadioButton, ToggleButton, ImageButton,
RatingBar, ProgressBar, SeekBar, VideoView, DatePicker, CalendarView, Spinner
2. Write an android code to make phone call using Intent
3. Write an android code to turn ON/OFF Bluetooth
4. Write an android code to turn ON /OFF the Wi-Fi
5. Design android application for login activity. Write android code to check login
credentials with username = "mca" and password = "android". Display
appropriate toast message to the user.
6. Create a fragment that has its own UI and enable your activities to communicate
with fragments.
7. Demonstrate Array Adapter using List View to display list of fruits.
8. Write an application to demonstrate Alert Dialog Box in android
9. Demonstrate Options Menu, Context Menu and Popup Menu in android
10. Write an application to produce Notification
11. Write an android application using SQLite to create table and perform CRUD
operations (Example. COURSE table (ID, Name, Duration, Description), perform
ADD, UPDATE, DELETE and READ operations)
12. Create an Android app, powered by Firebase Realtime database that supports:
Adding Data to Firebase Realtime database, Retrieving Data from Firebase and
Deleting data from firebase data.
13. Demonstrate WebView to display the web pages in an android application.
14. Write an android app to write JSON data into a file and read JSON data from
created file.
15. Write an application to display a PDF as an image in React app using URL
16. Develop simple flutter application to open a browser using Android SDK
KR an AI, ML, DL
1. Find the correlation matrix.

2. Plot the correlation plot on dataset and visualize giving an overview of
relationships among data on iris data.
3. Analysis of covariance: variance (ANOVA), if data have categorical variables on
iris data.
4. Apply linear regression Model techniques to predict the data on any dataset.
5. Apply logical regression Model techniques to predict the data on any dataset.
6. Clustering algorithms for unsupervised classification.
7. Association algorithms for supervised classification on any dataset
8. Developing and implementing Decision Tree model on the dataset
9. Bayesian classification on any dataset.
10. SVM classification on any dataset
11. Text Mining algorithms on unstructured dataset
12. Plot the cluster data using python visualizations.
13. Creating & Visualizing Neural Network for the given data. (Use python)
14. Recognize optical character using ANN.
15. Write a program to implement CNN
16. Write a program to implement RNN
17. Write a program to implement GAN
18. Web scraping experiments (by using tools)
Course Code: ITC31
- 10 Hrs./Week 5 - 75 - 50 125
Course Description:
A mini project is an assignment that the student needs to complete at the end of every
semester to strengthen the understanding of fundamentals through effective application of
the subjects learnt.
Course Outcomes:
CO1: Create working project using tools and techniques learnt in this semester
(Create)
Course Structure:
1. Students are expected to undertake one mini project starting from first semester till
third semester.
2. The student may take up the mini project in first semester based on the courses
learnt in that semester and for every next semester the mini project may be based
on the courses learnt in the current semester along with all the subjects learnt in
earlier semesters.
3. The student may take up the project individually or in group. However, if project is
done in group, each student must be given a responsibility for distinct modules.
4. Selected project/module must have relevant scope as per the marks assigned and
must be carried out in the Institute.
5. Internal guide should monitor and evaluate the progress of the project on individual
basis through handwritten workbook (Project Diary) maintained by students
containing various project milestones with learnings and remarks from internal guide
for concurrent evaluation.
6. The Project Synopsis should contain an Introduction to Project clearly stating the
project scope in detail justifying enough scope for 125 marks. The project work will
carry 75 marks for internal assessment and 50 marks for external assessment.
8. Students are expected to upload mini-project on GITHUB as project repository of
the institution.
submission.
10. The project will be assessed internally as well as externally by the examiners
appointed by University. University may appoint Industry Experts as an external
examiner

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Savitribai Phule Pune University, Pune

Faculty of Commerce and Management

Programme Curriculum ( Sem. I & II)

1. Definition: Outcome Based Education:

2. MCA Programme Focus:

PO1: Apply knowledge of computing fundamentals, computing specialization, mathematics, and

The MCA programme is a combination of:

a. Three-Credit Courses (75 Marks each): 3 Credits each

5. Open Courses (OC):

Suggestive List of OPEN Courses

FOR SEMESTER I FOR SEMESTER II FOR SEMESTER III

6. Extra Reading and Certification:

7. Evaluation and Assessment:

For Internal Evaluation

1. Internal evaluation will be of 75 Marks. It will be distributed as follows

For External Evaluation

For Internal Evaluation and External Evaluation

Suggested components for Concurrent Evaluation (CE) are:

1. Case Study / Situation Analysis – (Group Activity or Individual Activity)

The medium of Instruction will be English.

14.Maximum Duration for completion of the Programme:

15.Structure of the Programme and detail syllabus of each course:

Sr. No. Topics Details Weightage No of

Extra reading: docs oracle docs

Extra Reading : OCA Java Programmer :I Exam Kathy

Extra Reading: Understanding and practicing above

Extra Reading: Oracle Java tutorial

Extra Reading: Oracle Java tutorial

Extra Reading : Java arrays, tokenizer applications–

Extra Reading : Animation Using Thread

Extra Reading : regex – Pattern matching, split

Extra Reading : Using Swing toolkit GUI –oracle java

Extra Reading : Hierarchy of Event Classes, Event

Extra Reading : searching, sorting, insertion,

Extra Reading : Session handling 4 methods, Request

Recommended Learning Material:

Sr. No. Topics Details Weightage No of

Extra Reading: Circular Linked list and Circular doubly

Extra Reading: Application of Tree, B* tree

Extra Reading: Hashing used in File handling

Extra Reading: Application in Cryptography

8 Divide and Conquer 10 8

Extra Reading: Cooley–Tukey Fast Fourier Transform

Extra Reading: Painting Fence Algorithm, Moser-de

Extra Reading: Word Break Problem using Backtracking

1. Jean Paul Tremblay, Paul G. Sorensons, “AN Introduction to Data Structures

1. Lipschutz Schaum’s, “Data Structure”, Outline Series, MH

Sr. No. Topics Details Weightage No of

Extra Reading: Object oriented concepts

Note: Case studies based on SRS

Extra Reading: Fact finding techniques, Feasibility study

3. Use-case Driven Object-Oriented Analysis 40 20

3.2. Behavioral Diagram

3.2.2. Activity Diagram

Note: Case studies should be covered on the above topic

Extra Readings: UML diagram drawing tools such as

Note: Case studies should be covered on the above topic

Extra Readings: UI/UX software, Interactive UI design