The editors at Solutions Review have compiled this list of the best Python courses on Coursera to consider for growing your skills.
Python is an object-oriented programming language comparable to Perl, Ruby, Scheme, and Java. It utilizes an elegant syntax that makes the programs you write easier to read, and it is ideal for prototype development and other ad-hoc tasks. Python comes with a large standard library that supports many common programming tasks as well, including connecting to web servers, searching text with expressions, and reading and modifying files. The language can be extended by adding new modules as well.
With this in mind, we’ve compiled this list of the best Python courses on Coursera and online training to consider if you’re looking to grow your data analytics skills for work or play. This is not an exhaustive list, but one that features the best Python courses on Coursera and training from trusted online platforms. This list of the best Python courses on Coursera below includes links to the modules and our take on each.
The Best Python Courses on Coursera
OUR TAKE: The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this University of Michigan course.
Description: This course aims to teach everyone the basics of programming computers using Python. Instructors cover the basics of how one constructs a program from a series of simple instructions in Python. This course will cover Chapters 1-5 of the textbook Python for Everybody. Once a student completes this course, they will be ready to take more advanced programming courses. This course covers Python 3.
OUR TAKE: This course shows you how to scrape, parse, and read web data as well as access data using web APIs. Students will work with HTML, XML, and JSON data formats in Python.
Description: This course will cover Chapters 11-13 of the textbook Python for Everybody. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook such as variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files
OUR TAKE: By the end of this course, you’ll understand the benefits of programming in IT roles, be able to write a simple program, and figure out how the building blocks of programming fit together.
Description: This course is designed to teach you the foundations in order to write simple programs in Python using the most common structures. No previous exposure to programming is needed. Students start off by diving into the basics of writing a computer program. Along the way, you’ll get hands-on experience with programming concepts through interactive exercises and real-world examples.
OUR TAKE: No prior experience is necessary to take this training, which will show you how to create basic programs, work with data, and solve real-world problems in Python. More than 13 percent received a tangible career benefit from it.
Description: Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. This course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills.
OUR TAKE: The first course in Coursera’s Python 3 Programming Specialization, this training is best for beginners and those in need of a refresher. The module has no prerequisites so all skill levels are welcome.
Description: This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. You’ll program an on-screen Turtle to draw pretty pictures and also learn to draw reference diagrams as a way to reason about program executions, which will help to build up your debugging skills.
OUR TAKE: This beginner-level training takes roughly 13 hours to complete and covers topics like importing data, cleaning it, data frame manipulation, data summarization, and building machine learning regression models.
Description: Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Data Analysis with Python will be delivered through lecture, lab, and assignments
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