Programming for Data Science Syllabus   

Learn to use Python and SQL to solve problems with data  
 

Before You Start 

Prerequisites:​ There are no prerequisites for this program, aside from basic computer 
skills. You should feel comfortable performing basic operations on your computer (e.g., 
opening files, folders, and applications, copying and pasting). 
 
Educational Objectives:​ Students will learn the programming fundamentals required for a 
career in data science. By the end of the program, students will be able to use Python, SQL, 
the terminal, and git. 
 
Length of Program:​ 100 Hours* 
Program Structure:​ Self-paced, 3 months of access 
Textbooks Required:​ None 
Student Services:  
● Content: This includes video lectures, interactive quizzes, and other learning 
material.  
● Project Reviews, technical forums, weekly office hours, mentorship, Slack 
community 
 
*The length is an estimation of total hours the average student may take to complete all 
required coursework, including lesson and project time. Actual hours may vary. 
 
 
   
Project 1: Investigate a Database (45 hours) 
In this project, you’ll work with a relational database while working with PostgreSQL. You’ll 
complete the entire data analysis process, starting by posing a question, running 
appropriate SQL queries to answer your questions and finishing by sharing your findings. 

Supporting Lesson Content: Introduction to SQL 

Lesson Title  Learning Outcomes 

Basic SQL  ➔ Write common SQL commands including SELECT, 

FROM, and WHERE 
➔ Use logical operators like LIKE, AND, and OR 

SQL Joins  ➔ Write JOINs in SQL, as you are now able to combine 
data from multiple sources to answer more complex 
business questions 
➔ Understand different types of JOINs and when to use 
each type 

SQL Aggregations  ➔ Write common aggregations in SQL including COUNT, 

SUM, MIN, and MAX 
➔ Write CASE and DATE functions, as well as work with 
NULLs 

Advanced SQL Queries  ➔ Use subqueries, also called CTEs, in a number of 
different situations 
➔ Use other window functions including RANK, NTILE, 
LAG, LEAD new functions along with partitions to 
complete complex tasks 

Project 2: Explore US Bikeshare Data (45 hours) 

You will use Python to answer interesting questions about bikeshare trip data collected 
from three US cities. You will write code to collect the data, compute descriptive statistics, 
and create an interactive experience in the terminal that presents the answers to your 
questions. 
 
Supporting Lesson Content: Introduction to Python Programming 
In this part, you’ll learn to represent and store data using Python data types and variables, 
and use conditionals and loops to control the flow of your programs. You’ll harness the 
power of complex data structures like lists, sets, dictionaries, and tuples to store collections 
of related data. You’ll define and document your own custom functions, write scripts, and 
handle errors. You will also learn to use two powerful Python libraries - Numpy, a scientific 
computing package, and Pandas, a data manipulation package. 
 
Lesson Title  Learning Outcomes 

WHY PYTHON  ➔ Gain an overview of what you’ll be learning and doing in 
PROGRAMMING  the course 
➔ Understand why you should learn programming with 
Python 

DATA TYPES AND  ➔ Represent data using Python's data types: integers, 
OPERATORS  floats, booleans, strings, lists, tuples, sets, dictionaries, 
compound data structures 
➔ Perform computations and create logical statements 
using Python’s operators: Arithmetic, Assignment, 
Comparison, Logical, Membership, Identity 
➔ Declare, assign, and reassign values using Python 
variables 
➔ Modify values using built-in functions and methods 
➔ Practice whitespace and style guidelines 

CONTROL FLOW  ➔ Write conditional expressions using if statements and 

boolean expressions to add decision making to your 
Python programs 
➔ Use for and while loops along with useful built-in 
functions to iterate over and manipulate lists, sets, and 
dictionaries 
➔ Skip iterations in loops using break and continue 
➔ Condense for loops to create lists efficiently with list 
comprehensions 

FUNCTIONS  ➔ Define your own custom functions 

➔ Create and reference variables using the appropriate 
scope 
➔ Add documentation to functions using docstrings 
➔ Define lambda expressions to quickly create anonymous 
functions 
➔ Use iterators and generators to create streams of data 

SCRIPTING  ➔ Install Python 3 and set up your programming 

environment 
 ➔ Run and edit python scripts 
➔ Interact with raw input from users 
➔ Identify and handle errors and exceptions in your code 
➔ Open, read, and write to files 
➔ Find and use modules in Python Standard Library and 
third-party libraries 
➔ Experiment in the terminal using a Python Interpreter 

NUMPY  ➔ Create, access, modify, and sort multidimensional 

NumPy arrays (ndarrays) 
➔ Load and save ndarrays 
➔ Use slicing, boolean indexing, and set operations to 
select or change subsets of an ndarray 
➔ Understand difference between a view and a copy of 
ndarray 
➔ Perform element-wise operations on ndarrays 
➔ Use broadcasting to perform operations on ndarrays of 
different sizes. 

PANDAS  ➔ Create, access, and modify the main objects in Pandas, 

Series and DataFrames 
➔ Perform arithmetic operations on Series and 
DataFrames 
➔ Load data into a DataFrame 
➔ Deal with Not a Number (NaN) values 

 
 
Project 3: Post your work on Github (12 hours) 
 
In this project, you will learn important tools that all programmers use. First, you’ll get an 
introduction to working in the terminal. Next, you’ll learn to use git and Github to manage 
versions of a program and collaborate with others on programming projects. In this project 
you will post two different versions of a Jupyter Notebook capturing your learnings from 
the course, and add commits to your project Git repository. 

Supporting Lesson Content: Introduction to Version Control 

Lesson Title  Learning Outcomes 

SHELL WORKSHOP  ➔ The Unix shell is a powerful tool for developers of all sorts. 
  Get a quick introduction to the basics of using it on your 
computer. 

PURPOSE &  ➔ Learn why developers use version control and discover ways 
TERMINOLOGY 
 you use version control in your daily life 
➔ Get an overview of essential Git vocabulary 
➔ Configure Git using the command line 

CREATE A GIT REPO  ➔ Create your first Git repository with git init 
➔ Copy an existing Git repository with git clone 
➔ Review the current state of a repository with the powerful git 
status 

REVIEW A REPO’S  ➔ Review a repo's commit history git log 

HISTORY  ➔ Customize git log's output using command line flags in order 
to reveal more (or less) information about each commit 
➔ Use the git show command to display just one commit 

ADD COMMITS TO A  ➔ Master the Git workflow and make commits to an example 
REPO  project 
➔ Use git diff to identify what parts of a file have been changed 
in a commit 
➔ Learn how to mark files as "untracked" using .gitignore 

TAGGING,  ➔ Tagging, Branching, and Merging 

BRANCHING, AND  ➔ Organize your commits with tags and branches 
MERGING  ➔ Jump to particular tags and branches using git checkout 
➔ Learn how to merge together changes on different branches 
and crush those pesky merge conflicts 

UNDOING CHANGES  ➔ Learn how and when to edit or delete an existing commit 
➔ Use git commit's --amend flag to alter the last commit 
➔ Use git reset and git revert to undo and erase commits