15 Data Science Summer Pre-College Programs for High School Students
If you are a high school student interested in data science, a pre-college program can help you build foundational skills while exploring how data is collected, analyzed, and interpreted. These programs often introduce topics such as programming, statistics, machine learning, and data visualization through coursework, coding exercises, and independent or collaborative projects. They can also help you understand how data science is applied across fields such as healthcare, public policy, business, engineering, and scientific research.
What are the benefits of a data science pre-college program?
Data science pre-college programs introduce you to core skills such as programming in Python or R, working with datasets, and applying statistical methods to analyze data. Many programs include components where you build and test machine learning models, visualize data, or complete small research projects. Some also emphasize interdisciplinary applications, showing how data science connects to fields such as public policy, healthcare, and marketing. You may also gain experience with field tools, such as data visualization platforms or statistical software, and learn to communicate findings clearly through presentations or reports.
To help you get started, here are 15 data science summer pre-college programs for high school students.
If you’re looking for online summer programs, check out our blog here.
1. UChicago Data Science Institute Summer Lab
Location: University of Chicago, Chicago, IL
Stipend: $5,600
Acceptance rate/cohort size: 20-25 students
Dates: June 15 – August 7
Application Deadline: January 12
Eligibility: High school students in the Chicago area
DSI Summer Lab places you in a research lab environment where you work on interdisciplinary projects alongside mentors. You’ll be matched with a research area based on your interests, which may include applications in public policy, climate science, or biomedical research. Throughout the program, you engage with data science methodologies such as data analysis, research design, and collaborative problem-solving. You’ll also practice communicating your findings through presentations, including a final project shared in a conference-style setting. In addition to research work, the program includes discussions with professionals working in data science and related fields.
2. MITES Summer
Location: Massachusetts Institute of Technology, Cambridge, MA
Cost/Stipend: None
Acceptance rate/cohort size: Highly selective
Dates: 6 weeks in the summer
Application Deadline: February 1
Eligibility: 11th graders who are U.S. citizens/permanent residents
MITES Summer is a summer program for high school students that offers rigorous tracks in high-level math and science. You enroll in five college-level courses, including core electives in subjects like computer science, machine learning, and more. The curriculum goes beyond basic coding to include linear algebra and calculus necessary for high-level data analysis. You’ll also engage in lab tours and college admissions counseling. In addition to technical training, the program emphasizes technical writing and presentation skills, culminating in a final symposium.
3. Columbia University Pre-College Programs: Data Science & Machine Learning 1
Location: Columbia University, New York, NY/Virtual
Cost: $12,838 (residential), $6,381 (commuter), $4,018 (online); financial aid available
Acceptance rate/cohort size: 20 students/cohort
Dates: Summer A: June 29 – July 17 (July 6 – 17 for online); Summer B: July 21 – August 7 (July 20 – 31 for online)
Application Deadline: Summer A: April 20 (May 18 for online); Summer B: May 11 (June 1 for online)
Eligibility: High school students (15+)
This pre-college data science summer program introduces you to the relationship between data science and machine learning through real-world examples and applications. You begin with a broad overview of how these fields are used across industries, then move into hands-on work with Python to build foundational coding skills. The course emphasizes core machine learning algorithms and how they are applied to analyze data. Along the way, you examine ethical considerations in data analysis and how to communicate findings clearly. By the end, you’ll have developed the ability to interpret datasets and present insights in a structured way. The curriculum is designed for high school students with little to no prior programming experience.
4. Summer@Brown: Introduction to Machine Learning
Location: Brown University, Providence, RI
Cost: $3,748 (residential), $3,096 (commuter); scholarships available
Acceptance rate/cohort size: Not specified
Dates: July 13 – 17
Application Deadline: May 15
Eligibility: High school students aged 14–18
Summer@Brown offers pre-college programs where you can explore data science, including the vocabulary and techniques of machine learning. This course introduces learning in the context of ML, supervised, unsupervised, and reinforcement learning methods, generative AI, and the risks and ethics of decision-making through machine learning. It covers the basics of machine learning like linear regression, k-nearest neighbors, decision trees, clustering, mapping, pattern recognition, transformers, and more. You’ll get hands-on experience with ML libraries in Python and start building your own ML projects. Overall, you’ll get a working understanding of how machine learning systems work across a variety of fields and how to navigate them.
5. Cornell Precollege Studies: Introductory Statistics and Data Science
Location: Virtual
Cost: $7,760 (financial aid available)
Acceptance rate/cohort size: Selective
Dates: June 1 – 18
Application Deadline: April 28
Eligibility: Students who have completed their sophomore year and are 15–19 years old
This pre-college program introduces you to statistical thinking as a foundation for working with data. You study methods such as data collection, probability, and inference, using tools like regression and contingency tables to analyze relationships. The course incorporates statistical software and simulations to help you explore concepts through experimentation. Rather than focusing on a single field, you work with datasets from a range of real-world contexts. You also learn how to interpret results and evaluate the reliability of conclusions drawn from data.
6. Duke Pre-College: Introduction to Artificial Intelligence
Location: Duke University, Durham, NC
Cost: $6,050 (scholarships available)
Acceptance rate/cohort size: Not specified
Dates: July 13 – 24
Application Deadline: Rolling
Eligibility: High school sophomores, juniors, and seniors (14+) with a minimum 3.0 GPA
This summer pre-college program explores how artificial intelligence systems use data and algorithms to make decisions. You examine core concepts such as machine learning, computational thinking, and data-driven modeling through guided activities. The course also addresses ethical issues, including bias and data privacy, and how they affect AI systems in practice. As part of the program, you design a conceptual project that outlines how an AI system would solve a real-world problem using data. You’ll be required to analyze both the technical and societal aspects of your proposed solution.
7. Northwestern CTD: Data Science: Introduction to Statistics
Location: Northwestern University, Evanston, IL
Cost: $3025 + $2405 (residential fee); financial aid available
Acceptance rate/cohort size: Selective
Dates: June 28 – July 17
Application Deadline: One week before the start date
Eligibility: High school students who qualify for the relevant eligibility tier
In this data science program, you explore how statistical methods are used to interpret and model large datasets. You learn probability theory and apply it to real-world scenarios, including forecasting and decision-making. Using tools such as R or Python, you visualize data, run simulations, and test the validity of models. The course includes an independent research component where you identify a dataset, analyze it, and draw conclusions based on your findings. You also examine how data is used in areas like politics and sports to generate predictions.
8. Johns Hopkins Pre-College: Big Data and Advertising
Location: Johns Hopkins University, Baltimore, MD
Cost: $6,140
Acceptance rate/cohort size: Selective
Dates: Session Two: July 6 – 16; Season Three: July 20 – 30
Application Deadline: March 10
Eligibility: Students who have completed the 9th grade and have a minimum 3.0 GPA
In this data science summer program, you examine how large datasets are used to shape advertising strategies and consumer targeting. You explore how data is collected and analyzed, along with the role of predictive models in anticipating user behavior. The course integrates concepts from psychology, economics, and computer science to show how data-driven decisions are made in marketing contexts. You also work with Python to manipulate datasets and identify patterns relevant to advertising campaigns. Ethical considerations, such as data privacy and the use of personal information, are a key part of the curriculum.
9. WPI Frontiers: Data Science: Extracting Knowledge & Insights
Location: Worcester Polytechnic Institute, Worcester, MA
Cost: $4,495 (tuition assistance available)
Acceptance rate/cohort size: Selective
Dates: July 19 – 31
Application Deadline: April 30
Eligibility: Rising 10th to 12th graders
This pre-college summer program focuses on how you can use data to communicate insights clearly and effectively. You work with tools like Tableau to explore data visualization techniques beyond basic charts, emphasizing how to structure findings into a narrative. The course introduces core data science concepts, including data collection, statistical analysis, and interpretation. Through hands-on exercises, you practice transforming raw data into presentations that highlight meaningful patterns. The structure combines applied data work with an introduction to presenting results clearly and audience-focused.
10. NYU Tandon Machine Learning (ML)
Location: NYU Tandon School of Engineering, Brooklyn, NY
Cost: $3,180 + $654 (housing) and $229 (meal plan)
Acceptance rate/cohort size: Selective
Dates: Session 1: June 15 – 27; Session 2: July 6 – 17; Session 3: July 20 – 31
Application Deadline: April 17 (Session 1); May 1 (Session 2 & 3)
Eligibility: High school students (15+) who have completed precalculus and have some coding experience
This summer pre-college program for high school students provides a technical deep dive into the mathematical and programmatic foundations of machine learning. You spend the first week mastering linear regression, gradient descent, and data preprocessing techniques using libraries like NumPy and Pandas. The second week transitions into more advanced topics, including k-nearest neighbors, decision trees, and an introduction to neural networks. Every session includes hands-on coding labs where you implement these algorithms from scratch rather than just using pre-built libraries. The program concludes with a final challenge where you must build a model to predict outcomes from a novel dataset.
11. Wharton Data Science Academy
Location: University of Pennsylvania, Philadelphia, PA
Cost: $10,599 (financial aid available)
Acceptance rate/cohort size: ~75 students
Dates: June 21 – July 11; July 12 – August 1
Application Deadline: March 18
Eligibility: Students in grades 10-11 with a strong background in math and coding
This data science summer program introduces high school students to the foundations of data science through the lens of business and financial applications using the R programming language. You engage in rigorous coursework covering data visualization, wrangling, and statistical modeling to extract meaningful insights from large datasets. The curriculum emphasizes the entire data science pipeline, from data collection and cleaning to the application of machine learning algorithms. You’ll work in small teams to complete a capstone project in which you analyze a real-world dataset and present your findings to faculty. The program also features guest lectures by Wharton faculty and industry professionals on the role of data in modern decision-making.
12. MIT Beaver Works Summer Institute
Location: Virtual/Massachusetts Institute of Technology, Cambridge, MA
Cost: Free for families earning <$200,000; $2,400 otherwise
Acceptance rate/cohort size: Selective
Dates: July 6 – August 1 or 2
Application Deadline: March 30
Eligibility: U.S. 9th to 11th graders
This pre-college summer program offers project-based courses where you apply data science and machine learning concepts to real-world problems. In the CogWorks course, you work through modules focused on audio, vision, and language, using Python to implement algorithms and understand underlying mathematical concepts. The program emphasizes building systems from the ground up rather than relying on pre-built tools, which helps you understand how models function internally. In Medlytics, you apply machine learning techniques to medical datasets, tackling problems such as disease prediction and image classification. Across both tracks, you collaborate in teams using development tools such as version control systems.
13. UCLA Extension: Introduction to Data Science
Location: UCLA Extension Lindbrook Center, Los Angeles, CA/Virtual
Cost: $1,100 (financial aid available)
Acceptance rate/cohort size: Not specified
Dates: June 23 – August 25 (in person); June 22 – August 31 (online)
Application Deadline: April 5
Eligibility: Students with basic Python programming and statistics skills
This data science program introduces you to key areas such as data management, statistical analysis, and machine learning. You work with tools like Python, R, and SQL to explore how data is collected, processed, and analyzed. The course also covers topics such as natural language processing and data visualization, providing a broad overview of common techniques used in the field. You’ll engage with foundational concepts in statistics and exploratory data analysis to understand how insights are derived from datasets. The curriculum includes building and evaluating basic machine learning models. It is structured for students who already have some background in programming and statistics and want to deepen their understanding of data science methods.
14. Stanford Pre-Collegiate Summer Institutes: Introduction to Data Science
Location: Virtual
Cost: $3,200 (financial aid available)
Acceptance rate/cohort size: Selective
Dates: Session One: June 15 – 26; Session Two: July 6 – 17
Application Deadline: March 13
Eligibility: Students in grades 9–11 who have a working knowledge of statistics and exposure to a programming language
In this data science summer program, you examine how algorithms and models are used to analyze real-world datasets. You work with data from both natural and social sciences, applying machine learning techniques through hands-on exercises in R. The course introduces multiple modeling approaches, encouraging you to compare their strengths and limitations. You also explore how ethical considerations shape the use of data in decision-making. By the end, you’ll be able to approach unfamiliar datasets with a structured, data-driven methodology.
15. Harvard’s Pre-College Summer Program: Introduction to Python for Scientists
Location: Harvard University, Cambridge, MA
Cost: $6,100 (financial aid available)
Acceptance rate/cohort size: ~15 students/class
Dates: July 20 – 31
Application Deadline: February 11
Eligibility: Rising juniors and seniors who are 16–18 years old
This summer pre-college program focuses on building programming skills through scientific applications of Python. You learn core concepts such as variables, functions, and data structures, then apply them to datasets drawn from fields like biology, chemistry, and physics. The course introduces how coding supports tasks like data analysis, visualization, and interpretation in research settings. You also work with commonly used scientific computing libraries to process and explore data. The structure emphasizes consistent practice, with each session building on prior concepts.
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