Using Python for Research (edX)

In this course, after first reviewing the basics of Python 3, we learn about tools commonly used in research settings. This version of the course includes a new module on statistical learning.

Using a combination of a guided introduction and more independent in-depth exploration, you will get to practice your new Python skills with various case studies chosen for their scientific breadth and their coverage of different Python features.

What you'll learn:

- Python 3 programming basics (a review)

- Python tools (e.g., NumPy and SciPy modules) for research applications

- How to apply Python research tools in practical settings

Syllabus

Week 1: Python Basics

Review of basic Python 3 language concepts and syntax.

Week 2: Python Research Tools

Introduction to Python modules commonly used in scientific computation, such as NumPy.

Weeks 3 & 4: Case Studies

This collection of six case studies from different disciplines provides opportunities to practice Python research skills.

Week 5: Statistical Learning

Exploration of statistical learning using the scikit-learn library followed by a two-part case study that allows you to further practice your coding skills.