Hands On Training

Using Python for Research

Harvard University

via

edX

Course Features

Duration

12 weeks

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Effort

4 hours per week

Teaching Type

Self Paced

Course Description

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.

Course Overview

International Faculty

Case Based Learning

Post Course Interactions

Case Studies,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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

What You Will 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

Course Content

Expand all sections

Module 1: Python Basics

Module 2: Python Research Tools

Module 3: Case Studies

Module 4: Statistical Learning

Course Instructors

Jukka-Pekka "JP" Onnela

Associate Professor of Biostatistics at Harvard University

JP is an Associate Professor of Biostatistics in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. He is also the director of the school's Health Data Science master's...