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Statistics for Data Science

Statisticians who can code and understand data science have an advantage in today’s competitive, dynamic job market. Learn to solve complex challenges with data.

About the Course

Statistics for Data Science is a highly practical, eight-week course that will provide you with the foundational tools to solve data science problems and prepare you to take the next steps in the world of machine learning.

You Will Learn To:

  • Leverage a data set to produce a specified set of results
  • Evaluate results and understand the concept of hypothesis testing
  • Perform a Principal Components Analysis (PCA) to provide meaningful insights on the original data set
  • Learn the intricacies of logistic regression, evaluate its outputs, and comprehend how a link function works
  • Perform multiple pairwise comparisons and analyze models with multiple categorical predictors
  • Build a classification model and interpret results
  • Present a start-to-finish analysis with meaningful insights on a data set using exploratory analysis dimension reduction, linear models, and classification models
Methodologies and Techniques:
You Will Be Able To:
  1. Solve data science problems and prepare to take the next steps in the world of machine learning
  2. Understand RStudio and its application
  3. Gain confidence handling and manipulating data
  4. Interpret data and be able to communicate it effectively
  5. Earn a certificate of completion from the University of Chicago and become part of the UChicago network

Request for Information

Career Outlook




The average annual base pay for a statistician in the US


The ranking of statistician in US News and World Report’s 2021 Best Jobs


The expected CAGR of the global data science platform size from 2020 to 2027

  • Analytics Consultant
  • Data Insight Analyst
  • Data Scientist
  • Machine Learning Specialist
  • Statistician

Meet Your Instructors

Gregory Bernstein
Gregory Bernstein, MSc
Statistics for Data Science

Gregory Bernstein works as a data scientist for Kinexon Sports and Media, a small branch of a German based company working with teams in the NBA, NFL and other professional leagues to monitor athletes’ movement and exertion, provide consultation regarding load management, and optimize in-game performance. Bernstein enjoys working in the startup environment and engages in analytical modeling, reporting and visualization, and product development. He earned a BA from Lafayette College in creative writing and economics in 2012 and graduated from the University of Chicago Master of Science in Analytics program in 2019. In addition to sports, Bernstein has a passion for teaching and education and has previously worked with the Princeton Review and as a TA for both the MS Analytics program and the Booth School of Business.

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Do you have questions?

University of Chicago

“By directly involving students in the challenge of securing the right data and exploring potential solutions, we’re equipping them with the foundational skills required to deliver tangible results to clients.”

– Greg Green, PhD, Associate Senior Instructional Professor and Director of the MScA Program at the University of Chicago

The University of Chicago Approach to Online Learning

Our online learning programs are crafted with your specific needs in mind. Programs combine e-learning with live, interactive sessions to strengthen your skill set while maximizing your time. We couple academic theory and business knowledge with practical, real-world application. Through online learning sessions, you will have an opportunity to grow your professional network and interact with University of Chicago instructors and your classmates.

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Are you ready to take a leap forward and immerse yourself
in a new learning experience? Click the button below to
download the brochure or schedule a call to request more information.
Gain valuable knowledge and skills that will
boost your career to the next level.

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