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HarvardX: Using Python for Research

4.2 stars
51 ratings

Take your introductory knowledge of Python programming to the next level and learn how to use Python 3 for your research.

12 weeks
2–4 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

350,027 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Nov 8

About this course

Skip About this course

This course bridges the gap between introductory and advanced courses in Python. While there are many excellent introductory Python courses available, most typically do not go deep enough for you to apply your Python skills to research projects. 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.

At a glance

  • Institution: HarvardX
  • Subject: Computer Science
  • Level: Intermediate
  • Prerequisites:

    Some previous Python programming experience (in any version of Python)

  • Language: English
  • Video Transcripts: اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated skills:Research, Python (Programming Language), Go (Programming Language)

What you'll learn

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  • 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

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.

More about this course

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HarvardX Honor Code

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX Nondiscrimination/Anti-Harassment Statement
Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

HarvardX Research Statement
HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

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