Intro to Data Science and Statistical Foundations Live Online Courses Start Jan 22! Enroll Now

Statistical Foundations for Data Science and Machine LearningLive Online

This course will serve as introduction to basic statistical principles that are often used by data scientists and applied statisticians. Many of the concepts will be reinforced by using the statistical programming language R, one of the two most popular languages for Data Science. The intent of this course is to expose students to common statistical issues and teach them how to avoid statistical fallacies. By the end of the course, students will have a fundamental understanding of many of the statistical principles that underlie machine learning and data science.

Attend a Free Sample Class
Greg video Course designed by Greg Ryslik, Vice President of Data Science, Mindstrong Health

Your Instructor

Paul trowbridge

Paul Trowbridge received advanced training in statistics, demography and sociology from the University of Washington and Rutgers University. He has worked in applied fields such as fMRI, epidemiology and public health, international relations, urban planning and micro-simulation modeling. He has taught statistics, data science and data visualization through New York University's School of Professional Studies.

Your Teaching Assistant

Gordon dri

Gordon is currently a student in the Master of Science in Analytics (MScA) program at the University of Chicago and will graduate in March 2018. Prior to graduate school, Gordon studied Applied Science and Engineering at the University of Toronto where his undergraduate thesis developed novel approaches in algorithmic trading. Since arriving at the University of Chicago, Gordon has worked in research at the Harris School of Public Policy and Booth School of Business and interned as a quantitative analyst in commercial real estate investment at Magnolia Capital. Gordon thoroughly enjoys teaching and acts as a Teaching Assistant for Statistical Analysis, Data Mining and Linear and Non Linear Models in the MScA program at the University of Chicago.

Why Live Online?

Taught by world-class, data science practitioners.

Instructor and IPython notebook visible so you can follow along.

Private attention and real-time support from top-notch co-instructors.

Recordings available — catch up if you need to miss a class.

Live Online is social! Interact with instructors and classmates via chat.

Accessible wherever you have Internet access.

Register for an on-demand sample class!

Our 1-hour on-demand sample class is a great way to preview what the new Live Online experience is like for the Metis Statistical Foundations for Data Science and Machine Learning professional development course.

Paul Trowbridge, instructor of the Statistical Foundations for Data Science and Machine Learning course, will cover a few sample topics in the on-demand class:

  1. Bayes Theorem
  2. P-Values
  3. Cross Validation
  4. Law of Large Numbers


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