2023 High School Summer Camp

Introduction to Data Science and AI Camp

June 1216, 2023
University of Michigan,
Ann Arbor Campus

Registration is now closed.



2023 Introduction to Data Science and AI Summer Camp students

2023 Introduction to Data Science and AI Summer Camp students

What is data? What can it tell us about ourselves and our society? What is AI? How will it change our lives beyond self-driving cars and robots?

ChatGPT. Dall-E. Deep-fakes. Artificial intelligence and data science are more prevalent in society than ever before—but what, exactly, is going on? Students will have the opportunity to answer these questions and learn more about the basics of data science and AI at our annual Introduction to Data Science and AI High School Summer Camp. Campers will work with University of Michigan faculty, graduate students, and their peers to get a taste of data analysis, visualization, and AI through hands-on projects and instruction. Additional programming includes career explorations, presentations from the office of undergraduate admissions, and more.

Dates: June 12-16, 2023 (M-F, 9AM-5PM)

Location: U-M Ann Arbor Campus

Eligibility: High school rising juniors and seniors in Washtenaw and surrounding counties, with the preference that students have successfully completed at least geometry and algebra I & II or similar.

Camp cost: $15 – instructions for payment will be sent out with acceptance emails. A light breakfast and lunch will be provided each day of the camp.

MIDAS seeks to foster an accessible and inclusive data science and AI community, at U-M and beyond; we encourage students from demographic groups under-represented in STEM fields to apply, especially those who would not otherwise have the opportunity or means to attend such programs.

Questions? Reach out to midas-contact@umich.edu

About the Introduction to Data Science and AI Summer Camp


Day 1 - Computer vision, image analysis, image generation, fake images

In three sessions that combine lectures and hands-on exercises, campers will get a glimpse of how a computer program can detect what’s in a picture and generate a picture, and how to detect fake images.

Day 2 - Analyzing and visualizing data to understand human biology and behavior

How does a person’s height, weight, personality and other characteristics relate to their age, gender, and environment? Day two will introduce campers to data analysis and visualization. Campers will learn how data analysis can be used to illuminate patterns and relationships in large datasets, including real life applications in human biology and behaviors.

Day 3 - Words as data: analyzing texts and extracting meanings with Natural Language Processing

What does it mean when we say words (and texts) are data? How and why do we use AI to analyze texts? Campers will be introduced to Natural Language Processing, one of the most important data science and AI techniques.

Day 4 - Using data science in business operations; Ethical data science and AI

Can we predict the future by using data science? Students will learn how businesses use statistical forecasting to predict sales through a hands-on project led by data scientists from Domino’s.

The afternoon session will focus on the ethics of data science and AI.

Additionally, students will learn what a ‘day in the life of a data scientist’ looks like.

Day 5 - Words as data (part 2): analyzing sentiments and detecting misinformation

How does a computer ‘understand’ emotion? Building off of concepts from earlier in the week, day five will focus on NLP applications, introductions to Large Language Models (LLMs), and include hands-on activities to analyze sentiments and detect fake news.

About the Teachers

Paramveer Dhillon

Paramveer Dhillon

Assistant Professor of Information, School of Information, University of Michigan

Research Interests: Machine Learning, Information Systems, Data Science, & Computational Social Science
Andrew Owens

Andrew Owens

Assistant Professor of Electrical Engineering and Computer Science, College of Engineering, University of Michigan

Research interests: Fake image detection, multimodal perception, 3D reconstruction
Veronica Perez-Rosas

Veronica Perez-Rosas

Assistant Research Scientist, Electrical Engineering and Computer Science, College of Engineering, University of Michigan

Research Interests: Natural language processing, multi modal and cross-cultural approaches for deception detection and sentiment analysis, behavioral signal processing
Kerby Shedden

Kerby Shedden

Professor of Statistics, College of Literature, Science, and the Arts, Professor of Biostatistics, School of Public Health and Center Director, Statistical Consultation and Research, University of Michigan

Research Interests: Quantile and expectile analysis of clustered, longitudinal, and spatial data, regularized projection pursuit, mediation analysis


Contact Us


Message the MIDAS team: midas-contact@umich.edu