12 Competitive Data Science Programs for High School Students
Data science is one of the most exciting and fast-growing fields, shaping industries like healthcare, finance, entertainment, and sports. It’s all about using data to solve problems, make predictions, and uncover patterns that can drive important decisions. From designing recommendation systems like those on Netflix to helping doctors diagnose diseases with AI, data science plays a crucial role in how the world operates.
Data science is a great field to explore if you're interested in math, coding, or problem-solving. However, getting started can feel overwhelming—where do you even begin? That’s where competitive data science summer programs come in. These programs give you hands-on experience with real-world projects, introduce you to industry tools, and connect you with like-minded peers and mentors. Competitive data science programs are also a great way to strengthen your college applications and prepare for future opportunities.
To help you find the best options, we’ve put together a list of 12 of the most competitive data science programs for high school students in 2025!
1. Harvard Pre-College Program: Introduction to Data Science with a Focus on Visualization
Location: Harvard University, Cambridge, MA
Cost: $5,800 program fee + $75 non-refundable application fee
Acceptance Rate: Selective
Dates:
Session I: June 22 – July 3
Session II: July 6 – July 18
Session III: July 20 – August 1
Application Deadline: February 12
Eligibility: Academically motivated students graduating from high school; at least 16 by the start of the program
The Harvard Pre-College Program offers a two-week course called "Introduction to Data Science with a Focus on Visualization," designed for high school students. It provides hands-on experience in data science, focusing on visualizing data to communicate insights effectively.
During the first week, you will learn to gather and clean data from the web and create basic visualizations using Matplotlib, a Python library. The second week focuses on improving visualization skills and creating interactive visuals with JavaScript. Throughout the course, you will work with real-world data, exploring topics like web scraping, data cleaning, and advanced visualizations through collaborative learning.
2. Veritas AI
Location: Virtual
Cost: Starts from $2,290. Need-based financial aid is available. You can apply here.
Acceptance Rate: Selective
Dates: Varies according to the cohort; the summer cohort starts in May. More info here
Application Deadline: Rolling; March 23 for early admission into the summer cohort
Eligibility: Ambitious high school students. To apply to the AI Fellowship program, applicants should have finished the AI Scholars program or have experience with AI concepts or Python.
Veritas AI is a competitive data science program run by Harvard graduate students for high school students passionate about artificial intelligence. If you’re looking to get started with AI, ML, and data science, check out the AI Scholars program. During this 10-session boot camp, you will be introduced to the fundamentals of AI & data science. You’ll also get the chance to work on real-world projects.
The AI Fellowship with Publication & Showcase program, on the other hand, is for more experienced students. During this program, you will get to work 1:1 with mentors from top universities on a unique, individual project. You will also get to work with the in-house publication team, which will help you secure publications in high school research journals. The fellowship encourages you to explore interdisciplinary approaches, enabling you to merge AI with various fields such as finance, medicine, sports, environmental science, and more! You can browse through some examples of past projects here.
3. Columbia University Pre-College Programs – Data Science and Machine Learning 1
Location: Virtual or in-person at Columbia University, New York, NY
Cost:
3-week residential program: $12,449
3-week commuter program: $6,300
1-week commuter program: $2,825
3-week online: $3,960 (single course enrollment)
Acceptance Rate: Selective
Dates: Multiple sessions in the summer:
In-person: June 30 – July 18; July 22 – August 8
Online: July 7 to July 18; July 21 – August 1
Application Deadline: April – March, depending on the session
Eligibility: High school students in grades 9-12; prior experience is not required
Columbia University’s Pre-College Programs offer several courses that cover data science, including one called "Data Science and Machine Learning 1." During this course, you will learn about the basics of data science and machine learning as well as how they impact daily life and business decisions. You will also gain hands-on experience with Python and learn key machine-learning algorithms. Through real-world projects, you will explore how data science influences different industries. You can attend this course either in person at Columbia University or online.
4. Lumiere Research Scholar Program
Location: Remote
Cost: Starts from $2,990
Acceptance Rate: Highly selective
Dates: 8 weeks. The summer cohort starts on June 2
Application Deadline: Varies based on cohort; the summer cohort deadlines are:
Early Admission: February 9
Priority Admission: March 9
Regular Admission I: April 13
Regular Admission II: May 11
Eligibility: High school students with a high level of academic achievement (an unweighted GPA of 3.3 out of 4); previous knowledge is not required
The Lumiere Research Scholar Program is a rigorous program tailored for high school students that offers extensive 1-on-1 research opportunities across a broad range of subject areas. During the program, you will be paired with a Ph.D. mentor, who will work with you 1-on-1 on an independent research project for over 12 weeks. You can choose research topics from subjects, such as psychology, physics, economics, data science, computer science, engineering, chemistry, international relations, and more. You can apply here.
5. The University of Chicago’s Data Science Institute (DSI) Summer Lab
Location: The John Crerar Library at the UChicago Hyde Park campus
Stipend: $4,800
Acceptance Rate: Selective
Dates: June 16 – August 8
Application Deadline: January 12
Eligibility: High school and college students located in the Chicago area. Familiarity with any of the following is preferred: Python, Java, C++, etc.
The DSI Summer Lab Program at the University of Chicago is an eight-week paid research opportunity for high school and undergraduate students. As a participant, you will get to work with mentors in fields, such as computer science, data science, social science, public policy, climate and energy policy, materials science, and biomedical research. No prior research experience is required, making it a great opportunity for students eager to learn. This program is a competitive data science program that will help you develop research and analytical skills while exploring diverse fields.
6. Wharton Global Youth’s Data Science Academy
Location: University of Pennsylvania, Philadelphia, PA
Cost: $100 non-refundable application fee + $9,799 (financial aid available)
Acceptance Rate/Cohort Size: Highly selective; 75 students selected based on academic excellence
Dates: July 13 – August 2
Application Deadline:
Priority Deadline: January 29
Final Deadline: April 2
Eligibility: High school students in grades 10-11, with a minimum 3.3 GPA and a background in math and coding
The Wharton Data Science Academy offers a hands-on learning experience led by expert instructors. During the program, you will work with real-world data sets, analyze case studies, and improve your ability to interpret and present data effectively. The program includes a final project where you collaborate in teams to apply what you have learned and present your findings. To make the program even more engaging, you’ll attend sessions where guest speakers provide insights into careers in data science and Wharton teaching assistants share their experiences.
7. Carnegie Mellon University (CMU) Pre College: CS Scholars Program
Location: Carnegie Mellon University, Pittsburgh, PA
Cost: Free
Acceptance Rate: Selective
Dates: June 21 – July 19
Application Deadline: March 1
Eligibility: 10th or 11th graders; at least 16 years old by the start of the program; U.S. citizens or permanent residents; 2 letters of recommendation required
The Carnegie Mellon Pre-College CS Scholars Program is a competitive data science program that introduces you to computer science and data science via lectures, hands-on projects, and industry engagement with top tech companies. For over four weeks, you will learn programming in Python, explore key computer science concepts, and work with data structures and algorithms for data analysis.
The program ends with a hands-on project where you apply your skills to solve real-world problems. It is ideal for those passionate about technology and data-driven problem-solving, offering a supportive and engaging learning environment. As a CS Scholar, you’ll also be able to attend program-related field trips and events.
8. ASPIRE by Johns Hopkins
Location: Johns Hopkins APL, Laurel, MD. Virtual + In-person options available
Stipend: Unpaid
Acceptance Rate/Cohort Size: ~10%; up to 200 students placed
Dates: June 24 – August 21
Application Deadline: February 15
Eligibility: U.S. high school juniors and seniors residing in the Washington-Baltimore Metro area; must be 15 years old; a minimum GPA of 2.8 is required.
The ASPIRE program by Johns Hopkins offers high school juniors and seniors the chance to participate in a competitive data science program where they can explore STEM careers in a supportive environment. As an intern, you will work with APL staff, attend workshops, solve problems in teams, receive mentorship, and take part in hands-on projects. If you are interested in data science, you can apply to either of the following placements: Mathematics and Data Analysis, Programming and Computer Science, Information Technology and Cybersecurity, Artificial Intelligence (AI) and Machine Learning, and so much more. You will have to choose one area of interest and can participate in person, hybrid, or virtually.
9. MIT Beaver Works Summer Institute – CogWorks
Location: Virtual
Cost: Free
Acceptance Rate: Highly selective
Dates:
Online Course: February 3 – June 20
Four-week Virtual Summer Institute: July 7 – August 3
Application Deadlines:
Online Course: Applications open in December and close in January of the next year
Summer Institute: March 3 – March 31
Eligibility: High school students who have completed their sophomore or junior years. Completion of the online course is mandatory to participate in the Summer Institute.
The CogWorks program at MIT’s Beaver Works Summer Institute gives you hands-on experience in building AI-powered assistants using machine learning and data science and forming a foundational part of the entire process. It begins with an online prep course on Python, Git, natural language processing, and machine learning. You will then join a four-week summer session, working in teams to design and test AI systems using tools like Amazon Alexa. The program includes daily lectures, interactive projects, and a final competition where teams present their AI assistants. This is a highly prestigious and competitive data science program to get into.
10. Stanford Pre-Collegiate Studies: Introduction to Data Science
Location: Stanford University, CA
Cost: $3,080
Acceptance Rate: Highly selective
Dates: June 16 – June 27 (Session 1); July 7 – July 18 (Session 2)
Application Deadline: March 20
Eligibility: Students in grades 8-11; should have completed AP Statistics or a computer science course
In this Stanford Pre-Collegiate Program, you will learn how data science helps us understand the world and solve real-world problems. You will also explore computer algorithms and different models, each with its strengths and limitations. Using real datasets from the natural and social sciences, you will work on questions that matter to you. Through hands-on R programming exercises, you will apply machine learning techniques. By the end of the course, you will have the coding skills and scientific approach needed to analyze any dataset effectively.
11. UC Berkeley Pre-College Program: Foundations of Data Analysis
Location: UC Berkeley, CA
Cost: Application fee: $25 | 8 weeks: $15,950 | 6 weeks: $14,650 | Scholarships available
Acceptance Rate: Highly selective
Dates:
8 weeks: June 23 – August 15
6 weeks: July 7 – August 15
Application Deadline: March 10
Eligibility:
Completed 10th or 11th grade by summer and returning to high school in the fall
Minimum B average (3.0 GPA, weighted or unweighted)
At least 16 years old by June 22
Must live in program-provided on-campus housing
UC Berkeley offers a competitive data science summer program for high school students to explore data analytics, data visualization, and data-driven decision-making. We recommend the Foundations of Data Science course to build a strong base for future learning. In this course, you will learn key programming and statistical concepts to analyze real-world data and solve practical problems.
The program also gives you a taste of college life. The residential track lets you live on campus, earn college credit, and fully experience university life. Plus, having data science credits in high school can strengthen your college application!
12. Brown Pre-College: AI, Data Science, and Machine Learning Program
Location: Brown University, Providence, RI
Cost: $5,314
Acceptance Rate: Selective
Dates: June 23 – July 18
Application Deadline: May 9
Eligibility: High school students. It is recommended that applicants have experience in computer programming (Python or R), statistics, and probabilities.
The Brown PreCollege AI, Data Science, and Machine Learning Program is a great opportunity for students interested in exploring data science and its applications. In this program, you'll learn about data analysis, visualization, statistical modeling, and machine learning algorithms—key skills in the field. You'll also work on a final project, using real-world data to build a machine-learning model or solve a complex problem. This program is ideal for students who are curious about data science and want to develop their analytical and computational skills.
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