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If you want to pursue 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 have compiled a list of Python programming courses, taught at some of the best universities around the world. Which you can take for free and learn to code from the comfort of your home.
Most of these courses do not assume any prior programming experience. And teach you the fundamentals of programming and computing. So you can take the first steps toward a career change or pivot by learning Python, even if you've never programmed before.
Let's start!
CS50 Introduction to Python Programming o CS50 Python is a beginner course aimed at students who want to learn Python, even if they have no 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 will take you from a complete 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 Introduction to Python Programming
Python for everyone It 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 with Python features 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:
- Python Basics
- 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 everyone
Introduction to computing and programming with Python from MIT teaches you the fundamentals of computer science using Python. This course does not assume any prior knowledge in programming and computing.
Its goal is to introduce the fundamentals of computing and programming even to those who specialize in fields other than computer science. Over the course of twelve lectures, he will learn both programming principles and the basics of Python.
These are some of the topics this course covers:
- Computing Basics
- 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 computing and programming with Python
CS106A: Programming Methodology Another comprehensive course is taught at Stanford 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 are interested in learning how to solve problems with Python, this course is for you. There are a good number of assignments in this course and working on 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.
- Classification
- Object-oriented programming
- Memory management
Course link: Programming methodology
Carnegie Mellon University (CMU), through its open learning initiative, offers a free program Computing Principles with Python course. Which introduces you to both Python and the fundamental principles of computer science.
You will learn about topics such as iteration and recursion. Additionally, you will learn about basic computer science topics such as cellular automata, encryption, and the limits of computing.
Here is an overview of the topics covered:
- Programming with Python
- Iterative processes
- recursive thinking
- Binary representation of data and instructions.
- cellular automaton
- Encryption methods
- Computability limits
Course link: Introduction to Computing with Python
I hope you found some useful resources for learning Python. You don't need to take all of these courses to master Python programming.
Some of you may want to learn the features of the language and use it for tasks like web scraping, working with databases, and the like. While others may be interested in a straightforward approach to problem solving and coding algorithms in Python.
So depending on your learning goals, you can choose one or more of these courses that you think are best suited for you. Happy learning!
Bala Priya C. is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more.
