Best Data Science Courses on Coursera in 2020

What courses to choose if you want to boost your Data Science career

Learning online became one of the most popular forms of learning. With great platforms like MIT OCWare, Udemy and Coursera, anyone at any level can find something to learn from. In this post I want to highlight top Data Science Courses available right now on Coursera.

You are just starting, you want to learn the basics of Python and how to compile your first data science models. You haven’t done much data science or statistics before, you’ve heard a couple of terms, but those are just buzzwords for you right now. You want to build your knowledge from the ground up.

Introduction to Data Science in Python from University of Michigan is one of the two most popular introductory courses right now. It doesn’t assume anything, you’ll start with Python, and then go through different data structures (pandas!) and how to manipulate them. Perfect for beginners. Another popular course from UMich is Python Data Structures, which is also recommended for beginners.

IBM Data Science is a professional certificate which is composed of 9 courses. It starts slowly by explaining what is Data Science, what methodology and tools one uses, to go into data processing and data visualization, to finally arrive at machine learning. This is a great certificate to have on your resume, whether you’re just starting or you’ve done a bit of data science already.

Last but not least, if you want to get into data science, you need learn some mathematics and statistics. Don’t worry, not that much, but still you should be comfortable with doing operations on vectors, matrices, know what is a mean, variance, bias and be able to compute some probabilities. This course explains just that: Data Science Math Skills from Duke University.

You have some experience, you’ve started to feel confident in Python, you’ve done some experiments and now you look to expand your knowledge. Machine Learning is probably what you should pick up at this point.

Machine Learning Specialization by University of Washington is a perfect way to start your adventure with machine learning. This course assumes you’re fine with Python, know data structures and takes you through fundamental concepts of machine learning: classification and clustering algorithms. 4 courses in 1 specialization.

Applied AI course by IBM is a great dive into deep learning and deploying deep learning models on a cloud. You will learn about deep learning frameworks like Keras and Tensorflow (if you don’t know about them already). It’s really about deployment.

You have at least a couple of years of experience, you’re an expert in Python and using data science to extract information. You’re looking to consolidate your knowledge, put it all together and see what’s the most recent developments in Data Science.

Machine Learning course by Andrew Ng offered at Stanford is now a classic. Coursera was co-founded by Andrew Ng and this was one of the very first course on the platform. There are more up-to-date courses, but this one still manages to show you a theory behind machine learning very well. Highly recommended!

Deep Learning specialization offered by deeplearning.ai, founded by Andrew Ng again, is a place to go for the most up-to-date knowledge about deep learning and its applications. Whether you want to get into convolution neural networks, tune your hyperparameters or just play around with LSTMs — this course has it all. It’s definitely the best online course I’ve seen so far about Data Science/Machine Learning at this level.