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Python is also the language of choice for machine learning and data analysis, with 70% of practitioners prefer Python over other similar languages. Hence, the demand for learning this language is high among beginners as well as experienced professionals. Here are the top 10 Python courses in 2023 for you to learn that will help you to get into the employer's good books.
The course serves as a friendly introduction to the world of programming. It assumes from the get-go that you have no experience whatsoever coding nor know how programs work. It then moves from concept to concept, helping you build a comprehensive understanding of the Python language. The course is broken down into 7 weeks, with each week containing about 4 hours of video lectures and programming tasks. The lectures themselves are based on the book that can be found on the accompanying course website, and they've been translated into 9 languages if English isn't your strong suit.
The course not only serves as an introduction to Python but also to the fundamentals of computer science, exposing learners to concepts every programmer can benefit from. The course is part of the Introduction to Python Programming Professional Certificate, which closely matches Georgia Tech's undergraduate introduction to computer science, providing you with the skills needed to explore more advanced concepts and prepare for the professional world. The course starts with an introduction to computing and explains how computers work. You'll learn the jargon of computing and understand how code processing works.
This course is designed to help students with very little to no computing background learn the basics of creating simple interactive applications in Python, although you'll need some background in high school mathematics. What separates this course from others is that it is project-based, encouraging you to build and research things from scratch, an invaluable skill for developers in the real world.
Apart from the material from Python for Everybody, you'll work on five scientific computing projects. Scientific computing is most commonly needed in specialized and technical industries, like engineering or data science. In each project, you will be given some starter code and will be tasked with completing it.
This course is a fairly comprehensive course on Python, teaching you most of the language's features. No prior experience with programming is needed for this course. By the end of the course, you'll have an understanding of Python's capabilities and be able to write simple programs in Python. Then, you'll be introduced to Python and its features. For example, you'll be able to identify, distinguish, and convert different types of data types in Python, you'll learn what functions are and the role they play in code reuse, and you'll learn about the logical and comparison operators Python offers, as well as conditional statements. The course also teaches you how comments can help make your code cleaner.
The main aim of the course is to provide students with a brief introduction to a variety of topics in computer science, focusing on breadth rather than depth. This is to give students a sense of what is possible when thinking about using computation to accomplish specific goals, be it in their studies or career. This course tries to mirror the on-campus experience at MIT, so it's challenging and comprehensive. In terms of prerequisites, you want to have some knowledge of high school algebra and be willing to stomach some math, because this computer science course doesn't shy away from that.
At the end of the course, you'll import your first Python package, NumPy. NumPy is a popular Python package used by data scientists and analysts. You'll learn the difference between NumPy arrays and regular Python lists, and you'll see how easy it is to compute and analyze data with NumPy. The course consists of 4 chapters, each about an hour long. After each lecture, you'll have the chance to apply what you've learned in the exercises.
This course is offered by the Raspberry Pi Foundation on FutureLearn. By the end of the course, you'll create your own text-based adventure game. The course begins by introducing you to objects, and explaining that pretty much everything is an object in Python. You'll learn about the methods associated with each object, and use Python's turtle module to draw multiple shapes of different colors and sizes on a canvas.
Using Python for Research, offered by Harvard University on edX, fills in the awkward gap between introductory and advanced Python courses for people in research who know some Python but are clueless about what to do with it. This course introduces people to Python modules and concepts commonly used in scientific computation, such as NumPy and SciPy, as well as statistical learning. It allows learners to climb the ladder from a knower to a doer, and apply their skills in practical settings.
This course is fairly comprehensive and introduces you to some topics other introductory courses normally don't offer, like regular expressions, web scraping, and GUI automation. Plus, as you might've guessed, this course is very hands-on and project-driven. You'll learn about control flow through the visual charts, giving you a good understanding of concepts like conditional statements, loops, and iterations. You'll create your own functions and learn about variable scoping in Python.
