What experience level is required for MITx: Quantitative Biology Workshop?

This course is aimed at the Intermediate level. Having some basic understanding of the topic will help you get the most out of the curriculum.

How long does it take to complete MITx: Quantitative Biology Workshop?

The total duration of the course is approximately 9 weeks. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

Do I get a certificate after completing MITx: Quantitative Biology Workshop?

Yes, a certificate of completion is included, which you can add to your professional profile or resume to showcase your newly acquired skills.

What careers is this course relevant for?

The skills taught in this course are highly relevant for professionals pursuing roles within Biology & Life Sciences and adjacent technical fields looking to upskill.

Biology & Life Sciences

MITx: Quantitative Biology Workshop

A workshop-style introduction to tools used in biological research. Discover how to analyze data using computational methods.

Intermediate FriendlyCertification IncludedSelf-Paced Learning

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₹8217

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🧠 Good for intermediate learners

⚠ May feel basic for advanced users

Learning Journey Context

Works well as a continuation after mastering Biology & Life Sciences fundamentals. It bridges the gap toward advanced, production-level engineering.

Career Relevance

Relevant for: Data Scientist, Data Analyst, Machine Learning Engineer.

Quick Facts

9 weeks

MITx

Intermediate

Self-Paced Online

Online Course

edx

English

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What You’ll Learn

Do you have an interest in biology and quantitative tools? Do you know computational methods but do not realize how they apply to biological problems? Do you know biology but do not understand how scientists really analyze complicated data? 7.QBWx: Quantitative Biology Workshop is designed to give learners exposure to the application of quantitative tools to analyze biological data at an Beginner level. The Biology Department of MIT has run this workshop-style course as part of a one-week outreach program for students from other universities. With 7.QBWx, we can give more learners from around the world the chance to discover quantitative biology. We hope that this series of workshops encourages learners to explore new interests and take more biology and computational courses.

We expect that learners from 7.00x Introduction to Biology - The Secret of Life or an equivalent course can complete this workshop-based course without a background in programming. The course content will introduce programming languages but will not teach any one language in a comprehensive manner. The content of each week varies. We want learners to have an introduction to multiple languages and tools to find a topic that they would want to explore more. We recommend that learners try to complete each week to find what interests them the most.

This workshop includes activities on the following biological topics: population biology, biochemical equilibrium and kinetics, molecular modeling of enzymes, visual neuroscience, global and single-cell gene expression, development, and genomics. The tools and programming languages include MATLAB, PyMOL, Python, and R. This course does not require learners to download MATLAB. All MATLAB activities run and are graded within the edX platform. We do recommend that participants download a few other free tools for the activities so that they learn how to use the same tools and programs that scientists use.

Workshop Content Creators and Residential Leaders

Gregory Hale, Michael Goard, Ben Stinson, Kunle Demuren, Sara Gosline, Glenna Foight, Leyla Isik, Samir El-Boustani, Gerald Pho, and Rajeev Rikhye

Residential Outreach Workshop Organizer and Creator

Mandana Sassanfar

See how this course curriculum compares with alternatives

Outcomes

Apply quantitative methods to biological problems.
Define computational vocabulary.
Write Python, MATLAB, and R code to analyze biological data.
Examine any protein structure in PyMOL.
Analyze how to answer a scientific question through a step-by-step thought process..

See side-by-side differences in learning outcomes