A HarvardX course on edX teaching Python for scientific research, covering how to use Python libraries such as NumPy, SciPy and Matplotlib for numerical work and data visualization.

Commenters call it an amazing, practical course for applying Python to research, and say its lessons are still useful years later.

On Reddit (3)

1. Strongly recommendsnondifferentiabler/learnmachinelearning2019in “What do you recommend doing after Andrew Ng's course?”▲ 10

   Yes, learning Python is a good idea. This course is amazing: https://www.edx.org/course/using-python-for-research. I've been doing research for a couple of years and I'm still drawing on the things I learned from it.

2. RecommendsPuzzledDriver8916r/learnprogramming2023in “Deciding programming language for Science and Maths visualisations.”▲ 1

   If you want to deal with more “numeric” things, I think you might want to learn “numpy” and “scipy”, and for data visualization, I think “matplotlib” and “bokeh” would be great for what you need, and all of those are just python packages! There’s an awesome course on edx that teaches those…

3. RecommendsDJDinosauriPodr/learnprogramming2017in “Completed CS50. What next?”

   There's another MOOC from HarvardX that might be a good fit. The course is *Using Python for Research*. Also, check out Coursera and Udacity for more ML/DS courses.

Related courses

• Machine Learning (Andrew Ng)Coursera · 240 recommenders
• Practical Deep Learning for Codersfast.ai · 112 recommenders
• CS231n: Convolutional Neural Networks for Visual RecognitionStanford University · 39 recommenders
• Deep Learning Specialization (Andrew Ng)Coursera · 31 recommenders
• Neural Networks for Machine Learning (Geoffrey Hinton)Coursera · 25 recommenders
• CS229 Machine LearningStanford University · 20 recommenders
• Learning From DataCaltech · 20 recommenders
• CS188 Introduction to Artificial IntelligenceUC Berkeley · 18 recommenders