June 12–16, 2023
University of Michigan,
Ann Arbor Campus
2023 High School Summer Camp
Introduction to Data Science and AI Camp
June 12–16, 2023
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, field trips across U-M’s campus, and more.
Dates: June 12-16, 2023 (M-F, 9AM-5PM)
Location: U-M Ann Arbor Campus
Eligibility: Washtenaw county high school rising juniors and seniors, 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.
Please note: applications will be considered on a rolling basis; once the camp is at capacity, we will create a wait-list and follow up with wait-listed applicants as spots become available.
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 firstname.lastname@example.org
2019 Summer Camp Video
Work with Us!
Attention U-M students: looking for summer employment? Join us! MIDAS seeks multiple teaching assistants (TAs) for the camp.
TAs should be comfortable working with Python, SQL, and Jupyter notebooks. Previous experience as a camp counselor, resident advisor, or similar community programming is strongly preferred. Applicants will need to be on-site, central campus, for the weeks of June 5 (training) and June 12 (camp dates) and will work approximately 50-60 hours altogether over the course of those two weeks. The rate is $20/hour.
To apply, please email Rachel Sutton (email@example.com) your resume and briefly describe your interest in the position, your experience in working with data science tools including Python, SQL, and Jupyter notebooks, and any relevant camp counseling or similar experience.
Day 1 - June 12th, 2023
Introduction to Text Modeling and Natural Language Processing (NLP). Campers will learn the basics of NLP and how computers use algorithms to find patterns in a large amount of words.
Day 2 - June 13th, 2023
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 - June 14th, 2023
Fake images are becoming more and more prevalent. Day three will focus on how computers create images based on how humans describe the images to them.
Day 4 - June 15th, 2023
Can we predict the future by using data science? Day four will introduce students to statistical forecasting, including a hands-on project led by data scientists from Domino’s. Additionally, students will learn what a ‘day in the life of a data scientist’ looks like.
Day 5 - June 16th, 2023
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 DhillonAssistant Professor of Information, School of Information, University of Michigan
Research Interests: Machine Learning, Information Systems, Data Science, & Computational Social Science
Andrew OwensAssistant Professor of Electrical Engineering and Computer Science, College of Engineering, University of Michigan
Research interests: Fake image detection, multimodal perception, 3D reconstruction
Veronica Perez-RosasAssistant 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 SheddenProfessor 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