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Your Introduction to Data Science is tuition-free

Get a taste of our bootcamps completely free of charge with no commitments.
You’ll learn the basics of coding and be assigned a personal mentor to help you if you get stuck.
Our continuing education module consists of two eight-week units that challenge students to find several ways to solve problems through data analysis. Our hands-on approach ensures the skills students acquire translate seamlessly into the workplace.

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Across both units in the module, students gain a comprehensive introduction to scientific computing, Python, and the related tools data scientists use to succeed in their work. Students will develop machine learning and statistical analysis skills through hands-on practice with open-ended investigations of real-world data.

All students receive complimentary access to a ready-to-use Python environment for the entire module. This allows students to gain first-hand experience with Python, pandas, and Jupyter Notebooks, and allows for immediate immersion into novel data science problems.

The Applied Data Science module is built by Worldquant University’s partner, The Data Incubator, a fellowship program that trains data scientists. Graduates earn a certificate upon completion of each unit to share and celebrate their professional development.

Students only need to fill out a short profile on their educational history and technical skillset to apply. The application takes less than 20 minutes to complete.

The Module

The Applied Data Science module is delivered entirely online so students can participate in continuing education

without disrupting their lives.

Students who successfully complete Unit I earn a certificate and an invitation to enroll in Unit II. Those who successfully complete Unit II earn an overall certificate. Students have the opportunity to complete either unit of the module with honors.

Across two units and sixteen weeks, students learn to source data relevant to a business problem or task, to summarize data in aggregate statistics and visualizations, and to model trends to showcase insights and make practical business decisions.

Unit l: Scientific Computing and Python for Data Science

In Unit I, students gain a comprehensive introduction to scientific computing, Python, and the related tools data scientists use to succeed in their work. Successful completion of Unit I is a required prerequisite for enrollment in Unit II.

Unit ll: Machine Learning and Statistical Analysis

In Unit II, students develop machine learning and statistical analysis skills through hands-on practice with open-ended investigations of real-world data. Students can expect to work with authentic public data sets from organizations like the NHS, or anonymized data on credit card defaults. This unit has a heavy emphasis on creative use of the tools of data science to solve problems from multiple perspectives.

How does the module work?

The Requirements

This is a true introduction to data science and can accomodate beginners with the right amount of foundational knowledge. This professional development opportunity does not require you to have any prior degrees.


To qualify for the course you must have experience with algebraic concepts such as functions and variables, which are frequently used in programming.


Preference is given to applicants with familiarity in programming fundamentals, basic statistics, linear algebra, and calculus.


Students should expect to commit roughly 8 to 10 hours per week between lecture videos, assignments and individual study.

What else do I need to take the module?