Skip to main content

Pathways in Data Science

Program(s): Immersion

This course is currently at capacity for students applying in the Extended round. We are admitting students to the waitlist only, and students who currently are on the waitlist will be given priority if places become available.

Learn how to glean insights and meaning from complex sets of data in this overview of a field with growing importance in business, government, and scientific research. Students will learn to use the transformational tools of data science and machine learning and see how researchers are applying them in various scientific and social science fields. Students will study how data is collected and stored and then how it is explored, visualized, and communicated. Using Python, students will learn techniques for classification, prediction, inference, and regression. Then, through group projects, students will use these techniques to study a data science problem of their own choice in small groups. Throughout the course, visiting guest lecturers will broaden students’ perspectives by sharing how data science is used in their diverse fields, ranging from business applications to biology.

See sample syllabus here.

Remote or Residential

✓ Residential (On-Campus)


Course Considerations

Students should have experience with programming (preferably Python) and ideally calculus through single variable calculus (AP Calculus AB or equivalent). Students without programming experience must complete a free online Python course before the beginning of the course; information will be available from instructors in the weeks before the course begins.

Coding Intensive

Course Overview

Start Date

July 10

End Date

July 26

Current Grade / Education Level

9th Grade
10th Grade
11th Grade



Class Details

Course Code

STAT 10118 94

Class Day(s)

Mon Tues Wed Thurs Fri

Class Duration (CST)


3:00 P.M.


Session II

Course Length

3 weeks

HS Orientation Date

July 08
July 09

Primary Instructor

Melissa Adrian

Secondary Instructor

Jimmy Lederman

Academic Interest

Examining Culture and Society
Math and Computer Science