In this article, we will explore the top 5 free Python programming courses in 2024, offered by prestigious institutions like Harvard, MIT, and Stanford. These courses provide a comprehensive introduction to Python, covering topics like data types, functions, libraries, and more. By enrolling in these courses, you can gain valuable knowledge and skills that can help you advance your career or pursue your interests. Whether you are looking to learn Python for data analysis, machine learning, or web development, these courses offer a great starting point.
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Table of Contents
Here Are the Top 5 Free Python Programming Courses in 2024
1.CS50’s Introduction to Programming with Python
An introduction to programming using a language called Python. Learn how to read and write code as well as how to test and “debug” it. Designed for students with and without prior programming experience who’d like to learn specifically. Learn about functions, arguments, and return values (oh my!); variables and types; conditions and Boolean expressions; loops; and objects and methods. Plus exceptions, file I/O, and libraries. Hands-on opportunities for lots of practice. Exercises inspired by real-world programming problems.
What you’ll learn?
functions, arguments, return values
variables, types, exceptions
conditionals, Boolean expressions
loops
objects, methods
file I/O, libraries
Course Link Click Here
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2.MITx: Introduction to Computer Science and Programming Using Python
This course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems.
Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses. This run features lecture videos, lecture exercises, and problem sets using Python 3.5. Even if you previously took the course with , you will be able to easily transition to Python 3.5 in future courses, or enroll now to refresh your learning.
Since these courses may be the only formal computer science courses many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, they are not “computation appreciation” courses.
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3.CS106A – Programming Methodology
This course is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing.
Programming Methodology teaches the widely-used Java programming language along with good software engineering principles. Emphasis is on good programming style and the built-in facilities of the Java language. The course is explicitly designed to appeal to humanists and social scientists as well as hard-core techies. In fact, most Programming Methodology graduates end up majoring outside of the School of Engineering.
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4. Principles of Computation with Python
This course provides an introduction to Python and elementary principles of computing, including iteration, recursion, and binary representation of data. Additional topics on cellular automata, encryption, and the limits of computation are also introduced.
The main goal of this course is to teach the fundamental principles used in computer science to a general audience so that they understand how computer scientists use these principles to solve complex problems to improve their daily lives. The first four modules employ to introduce and illustrate conditionals and iteration. The remaining modules do not use and can be used to can be incorporated into classes that do not use. Used together, these materials show students that there is much more to computer science than learning to write code.
Course Link Click Here
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5. Programming for Everybody (Getting Started with Python)
This course aims to teach everyone the basics of programming computers using . We cover the basics of how one constructs a program from a series of simple instructions in . The course has no prerequisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. This course will cover Chapters 1-5 of the textbook ” for Everybody”. Once a student completes this course, they will be ready to take more advanced programming courses. This course covers Python 3.
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FAQ
Is there a way to learn Free Python Programming Courses from these top universities?
Absolutely! All five courses listed in this guide are completely free to access and audit, meaning you can watch all the lectures and participate in forums without paying a dime. Some universities may offer optional paid certificates upon completion, but the core learning materials are open and accessible to everyone.
I already know some Python. Are there courses for me too?
Of course! The guide offers a diverse range of courses catering to various skill levels. Some delve deeper into advanced topics like machine learning and data science, while others focus on specificlibraries and frameworks used in professional settings. No matter your current skill level, there’s a course here to hone your expertise and propel you further on your journey.
Where do I find Free Python Programming Courses?
Don’t fret! Each course listed in the guide includes a direct link to its online platform, making it easy to jump right in and start learning. Whether it’s edX, Coursera, or another platform, we provide clear navigation to get you coding as soon as possible.
4. How much time do I need to dedicate to Free Python Programming Courses?
The time commitment varies depending on the course content and your learning pace. Some beginner-friendly courses can be completed in a few weeks, while advanced offerings might require several months of dedicated study. You can find estimated timeframes listed in the guide to help you plan your schedule. Remember, learning is a marathon, not a sprint, so set realistic goals and enjoy the process of mastering Python!
