Last Updated on April 6, 2020

In 2017, IBM developed their Data Science Professional Certificate on Coursera, which has continued to gain popularity. Please read on for that and the other best courses to learn data science in 2020.

Data Science is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence.

A basic grounding in the principles and practices around Data Science is becoming increasingly valuable, regardless of your field of business, expertise or profession.

So, I started creating a review-driven guide that recommends the best data science courses for each subject within Data Science and for this guide, I put a tremendous amount of efforts trying to identify every best data science course on the internet.

First off, If your understanding about Data Science is a big question mark, I’ve got a one practical read for you about How to Become a Data Scientist— Learning Python, Statistics and Maths.

Next, You need to have build a solid understanding of advanced statistical concepts for a more successful career in data science. If you need a to learn the basics or grasp advanced concepts, give this article about the Probability and Statistics for Data Science Courses a read.

Data Science is becoming very popular, so this piece will be updated at least once every quarter. Go ahead and save this one in your pocket/ bookmarks.☆

7 Data Science Courses from World-Class Educators

Data Science offers enormous potential and in this guide, for Best Data Science Courses we interrogate what’s possible.

Here’s curated a list of the best (and Affordable!!!) data science courses with professional specialization certification to upgrade your skills with applicability to real jobs that employers value.

IBM Data Science Professional Certificate **Our top choice**

IBM Data Science Professional Certificate is a specialization comprised of 9 courses, offered by IBM Cognitive Training team on Coursera.

The IBM Data Science Professional Certificate will introduce you to open source tools for performing data science tasks, statistical libraries, cloud services, datasets, Machine Learning algorithms, assignments and projects that will provide you with practical and latest job-ready skills.

Is it right for you?

This course is designed for the learner who has never used Python before and wants to learn more about data science using Python.

Hands-on exercises and projects are central to the syllabus, so if you prefer hands-on learning, you’ll definitely love this specialization.

Intro to Python for Data Science [ Highly Recommended ]

This course is created by Filip Schouwenaars who is a Data Science Instructor at DataCamp. Filip holds a degree in Artificial Intelligence and is the passionate developer behind several of DataCamp’s interactive classes, covering both R for Data Science and Data Science with Python Courses. This course focuses on Python specifically for data science and you will learn about powerful ways to store and manipulate data as well as cool data science tools to start your own analyses.

Is it right for you? This course is for an enthusiastic data science novice who’s committed to learning the essentials of the field from the ground up using Python. You don’t need any background in analytics or programming to learn Python.

Python for Data Science and Machine Learning Bootcamp Recommended ]

This comprehensive course is one of the best and highly rated course on the internet to learn Data Science and Machine Learning, rated 4.5 of 5 of 41k+ ratings. You will learn how to program with Python for Data Science and then how to create amazing data visualizations, and finally how to use Machine Learning with Python.

This course is offered by Pierian Data International on Udemy, designed for both beginners and experienced developers to jump start their career into Data Science and learn how to implement Machine Learning algorithms.

Is it right for you?

If you have a basic knowledge of Python, this course is suitable to learn Data Science and Machine Learning.

Upon the completion of this course, you will be able to use Python for Data Science and Machine Learning.

Data Science Specialization [ Highly Recommended ]

Data Science Specialization is a nine-course introduction to data science, created and taught by leading professors at John Hopkins University.

This specialization will equip you with the functional knowledge of R Programming, key statistical concepts, reproducible research for scientific claims, and Machine Learning.

Is it right for you?

Data Science Specialization is suitable for beginners with no programming experience or formal background in statistics or maths.

All the courses offered in this specialization will equip you with key concepts and tools you’ll need throughout the entire data science pipeline. For another specialization, please consider the IBM Data Science Professional Certificate above as well.

By the end of this course, you’ll have a set of data science skills to transform your data into actionable insight.

Data Scientist with Python Track Highly Recommended ]

Data Scientist with Python Track offered by DataCamp is comprised ofCourses, this learning track covers every major topic to equip students to create data-driven products which can be used to solve real-world problems.

Data Scientist with Python Career Track is designed to take you from novice (i.e. almost no knowledge of programming) to “Data Scientist” over the course of 22 courses.

DataCamp is really great and extremely good value for the price you pay. DataCamp offers over 200+ courses by expert instructors on topics such as importing data, data visualization, and machine learning.

Is it right for you?

This learning track is suitable for beginners who’ve never touched Python, to get familiarized with the language and how Python can help in achieving data analysis tasks and become a reliable and skilled practitioner of the art.

You will learn faster through DataCamp’s immediate and personalized feedback on every exercise and join thriving community of Data Scientists and Machine Learning Researchers to get help whenever.

This course is created by the University of Michigan and published on Coursera and has been rated 4.5 of 5, of 7,815 ratings.

This course is perfect for self-starters to learn the basics of the Python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating CSV files, and the numpy library.

Is it right for you?

The course will introduce you to the best-applied techniques for data manipulation and cleaning using Pandas, the data science and machine learning library in Python.

You will also learn the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively.

Learning Path – Applied Data Science with Python Specialization

Applied Data Science with Python is five-courses skills-based specialization offered by the University of Michigan , introducing learners to data science through Python.

This specialization will equip learners with the functional knowledge of using popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and network to gain insight into their data.

Is it right for you? You will learn the concepts to process or apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through open source tools and libraries in Python. This specialization requires basic knowledge Statistics for Data Science and or some coding experience in Python.

Data Science at Scale Specialization covers 4 intermediate courses in data science to help learners gain hands-on experience with scalable SQL and NoSQL data management solutions, data mining algorithms, and practical statistical and machine learning concepts.

You will also learn the Data Visualization techniques and explore legal and ethical issues that arise in working with big data.

Is it right for you?

You will learn and understand the efficient use of scalable data management, how to evaluate big data technologies, and design effective visualizations to the communicate results effectively. This specialization requires some background in programming and basic knowledge of data management solutions.

Thanks for making it to the end :~)

If you liked this article, I’ve got a practical reads for you one about the Maths for Data Science and one about Probability for Data Science.

I’ve also got this Data Science Newsletter that you might be into. I send a tiny email once or twice every quarter with some useful resource I’ve found. Don’t worry, I hate spam as much as you. Feel free to subscribe. ☟

Image Credits: Canva, Towards Data Science, Coursera, Udemy, DataCamp