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Online data science courses to jumpstart your future.

3 Best Python Courses in 2020

Python is the most popular language for data science and machine learning. 

As the most popular language for data science experiments and machine learning algorithms, Python is an essential tool for any data-oriented computer scientist. Whether you’re just starting your coding journey or you’re further along the way, there are many great sources to learn Python online. 

The best 3 Python courses are:

  1. Python for Everybody by University of Michigan
  2. Python3 Programming by University of Michigan
  3. Python for Data Science and AI by IBM

Let’s review them one by one.

Python for Everybody by University of Michigan

Python for Everybody by University of Michigan

Python for Everybody offered by University of Michigan is the most popular Python course on Coursera with over 1.2M students as of April 2020. And there’s a reason for that: it’s great and starts from zero (no experience assumed). The whole specialization — 5 courses in total — starts with the course which aims to teach everyone the basics of programming computers using Python. 

It covers the basics of how one constructs a program from a series of simple instructions in Python. 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 course. 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.

If you just want to start, you don’t have to do the whole specialization, just try with the first course and see how you like it

Python3 Programming by University of Michigan

Python3 Programming by University of Michigan

Python3 Programming offered by University of Michigan is another great course to start your coding journey with Python. 

This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance.

You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don’t work.

By the end of the specialization, you’ll be writing programs that query Internet APIs for data and extract useful information from them. And you’ll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer.

This specialization is a good next step for you if you have completed Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations like Applied Data Science with Python.

Python for Data Science and AI by IBM

Python for Data Science and AI offered by IBM is a gentle introduction to Python with Data Science in mind. This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. 

It’s a great choice if you’re looking to take other courses from IBM — there are plenty related to Data Science, with the most popular being IBM Data Science (over 1 million students!). 

Which Python course to choose?

Any of the above 3 courses is great to jump start your programming career, so just decide what direction you want to take — is it more data science oriented or software engineering oriented? 

You might also consider taking a Python certification from Edureka which runs a more in-depth career bootcamp related to Python.

If you’re looking for more materials to learn have a look at:

Finally you might want to read my book on what Data Scientists do and how to approach a career in Data Science.

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