Decision-Making with Data
Applying Data Science, Machine Learning, and AI to Real-World Problems
Program Description:
The question is not whether AI will change how decisions are made—it's whether you'll be equipped to shape those decisions.
In a world increasingly shaped by data and artificial intelligence, the ability to think critically about how decisions are made has never been more important. This five-day intensive program introduces high school students to the foundational concepts and hands-on tools that power modern data science, machine learning, and AI.
Students will learn to frame real-world problems as data questions—from healthcare and climate to social equity—and work through the full analytical pipeline: cleaning and exploring datasets, building predictive models, and evaluating their results. Using Google Colab and scikit-learn, participants will train machine learning models from scratch and interpret what those models actually tell us.
The program also ventures into the frontier of generative AI. Through direct work with the Gemini API, students will build AI-powered applications and develop the prompt-writing fluency that's fast becoming an essential professional skill. Equally important, participants will examine where AI systems fail—exploring bias, fairness, and the ethical responsibilities of anyone who builds or deploys these tools.
By the final day, students won't just understand how AI works—they'll be able to communicate data-driven insights to any audience, technical or not. Whether you're interested in medicine, policy, engineering, or social change, this program gives you the analytical foundation to contribute meaningfully to the data-driven world ahead.
Dates: Fall 2026
Location: Asynchronous Online with Live Synchronous Sessions
Price: $1,995
For more information or questions: Email tcacademy@tc.columbia.edu
Instructor
John Park, Ph.D.
Dr. John Park is a Principal Research Technologist at the Digital Futures Institute, where he researches AI in education and programming. He holds a Ph.D. in Cognitive Science and Applied Statistics from Teachers College, Columbia University, where he also serves as an Adjunct Assistant Professor teaching courses in Statistics, Machine Learning & Data Mining, Research Methods, and Sustainability & Climate Change.
Before pursuing his doctorate, Dr. Park spent 12 years as a high school science teacher—experience that shapes his hands-on, student-centered approach to instruction. He has also worked with ETS and the College Board designing assessments and analytics.
Dr. Park is Co-Director of the DEW Lab at Teachers College, a research group studying how environments—including climate change—affect human development and wellbeing. His research spans learning analytics, STEM education, curriculum design, and AI applications in education.
Learning Objectives
Upon successful completion of this course, students will be able to:
- Write and run Python code for data analysis in a cloud environment
- Frame real-world problems as rigorous, answerable data science questions
- Perform exploratory data analysis and create meaningful visualizations
- Train and evaluate a machine learning model and interpret its outputs
- Build AI-powered applications using a live large language model API
- Write effective prompts and understand LLM capabilities and limitations
- Identify sources of bias and ethical concerns in AI systems
- Communicate data-driven insights clearly to technical and non-technical audiences
Who Should Attend
TC Pre-College courses are open to students ages 14-17. All courses are conducted in English and learners should have sufficient fluency to participate.
This program is ideal for high school students who are curious about data, technology, and artificial intelligence — no prior experience required. Whether your interests lie in computer science, math, economics, or the social sciences, this program is a great fit for students who enjoy problem-solving and want hands-on exposure to the tools and concepts shaping today's data-driven world.
Upon Completion
Participants who successfully complete this program will earn a verified Certificate of Participation and an official Digital Badge—valuable credentials that can be shared on LinkedIn or digital portfolios.
View our sample program badge and certificate below:
