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If you want to make a career in data science or software engineering, Python is a great first language to learn. So where do you start?
To help you decide, we’ve compiled a list of Python Programming courses—taught at some of the best universities from around the world. Which you can take for free and learn to code from the comfort of your home.
Most of these courses assume no prior programming experience. And teach you both programming and computer science fundamentals. So you can take the first steps—towards a career switch or pivot by learning Python—even if you’ve never programmed before.
Let’s begin!
CS50’s Introduction to Programming with Python or CS50 Python is a beginner-friendly course targeting learners who want to learn Python—even if they don’t have prior programming experience.
You can access the lectures, lecture notes, and problem sets on the course website. Over the course of ten weeks, this course takes you from an absolute beginner to someone who is fluent enough to code applications in Python.
The course covers the following:
- Functions and variables
- Conditionals
- Loops
- Exceptions
- Libraries
- Unit tests
- File I/O
- Regular expressions
- Object-oriented programming
- Python best practices
Course link: CS50’s Introduction to Programming with Python
Python for Everybody is a highly recommended Python course. The course is taught by Dr. Charles Severance at the University of Michigan.
If you want to quickly get up to speed on the features of Python and start working with different types of data and applications such as web scraping and working with databases, this course is for you.
Here’s an overview of what you’ll learn:
- Basics of Python
- Python data structures
- File I/O operations
- Regular expressions
- Network programming
- Introduction to OOP
- Using web services with Python
- Working with databases in Python
- Data visualization
Course link: Python for Everybody
Introduction to Computer Science and Programming with Python from MIT teaches you computer science fundamentals using Python. This course does not assume any prerequisite knowledge in programming and computer science.
It aims to introduce the fundamentals of computation and programming even to those majoring in fields other than computer science. Over the course of twelve lectures, you get to learn both the principles of programming and the basics of Python.
Here are some of the topics that this course covers:
- Basics of computation
- Branching and iteration
- String manipulation, approximation, bisection etc.
- Decomposition, abstraction and functions
- Tuples, lists and related concepts
- Recursion and dictionaries
- Testing and debugging
- Object-oriented programming
- Program efficiency
- Searching and sorting
Course link: Introduction to Computer Science and Programming with Python
CS106A: Programming Methodology taught at Stanford is another comprehensive course to learn the basics of Python programming. This course also assumes no prior Python Programming experience, and is aimed at teaching beginners how to program in Python.
If you’re interested in learning problem solving with Python, this course is for you. There are a good number of assignments in this course and working through them will help you apply what you have learned.
The course covers the following topics:
- Variables and control flow
- Lists and images
- Lists of lists and strings
- File reading
- Nested structures
- Dictionaries and drawing
- Sorting
- Object-oriented programming
- Memory management
Course link: Programming Methodology
Carnegie Mellon University (CMU), through their open learning initiative, offers a free Principles of Computation with Python course. Which introduces you to both Python and the fundamental principles of computing.
You’ll learn about topics such as iteration and recursion. In addition, you’ll learn about core computer science topics such as cellular automata, encryption, and limits of computation.
Here is an overview of the topics covered:
- Programming with Python
- Iterative processes
- Recursive thinking
- Binary representation of data and instructions
- Cellular automata
- Encryption methods
- Limits of computability
Course link: Introduction to Computation with Python
I hope you found some helpful resources to learn Python. You don’t have to take all of these courses to become proficient in Python programming.
Some of you may be looking to learn the features of the language and use it for tasks such as web scraping, working with databases, and the like. While some others may be interested in a head-first approach to problem solving and coding up algorithms in Python.
So depending on your learning goals, you can choose one or more of these courses that you think are the best fit for you. Happy learning!
Bala Priya C is a developer and technical writer from India. She likes working at the intersection of math, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She enjoys reading, writing, coding, and coffee! Currently, she’s working on learning and sharing her knowledge with the developer community by authoring tutorials, how-to guides, opinion pieces, and more.
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