20 AI Summer Programs for High School Students
If you're a high school student interested in artificial intelligence, summer is a good time to work on deeper research in the field and gain the advanced knowledge you will need to succeed. University programs, research labs, and national institutes offer the kind of exposure to tools, methods, and mentors that a high school classroom can't provide. You'll work through real technical problems, hear directly from active researchers and practitioners, and get a ground-level view of what the field actually looks like from the inside.
What are the benefits of an AI program?
The work you'll do in these programs is much more practical than the pedagogy of a high school lecture. You could build a neural network that powers a self-driving toy car, work on a faculty-led research project using clinical health records, prototype an AI application designed to address a community problem, or analyze how AI systems intersect with public policy and questions of fairness. Some programs place you in a research lab alongside graduate students for several weeks, while others run shorter-term workshops intensely focused on specific subjects.
We've narrowed the list to 20 AI summer programs open to high school students.
If you’re looking for online summer programs, check out our blog here.
1. Carnegie Mellon University AI Scholars
Location: Carnegie Mellon University, Pittsburgh, PA
Cost: Fully funded
Acceptance Rate/Cohort Size: Not specified
Dates: June 20 – July 18
Application Deadline: February 1
Eligibility: High school juniors aged 16+ who are U.S. citizens or permanent residents
Over four weeks on CMU's campus, you'll move through college-level AI coursework, faculty-led lectures, and collaborative group projects that culminate in a final symposium presentation. The technical curriculum sits alongside weekly seminars on college admissions and financial aid, which means you'll leave with both a substantive AI project and a clearer picture of what comes next academically. No prior coding experience is required, and the program draws applications from first-generation college-bound students, those at schools with low college placement rates, and students underrepresented in STEM. Guest lectures bring in researchers and practitioners working in AI across industries, giving you exposure to the field's range over and above what the coursework alone covers.
2. Veritas AI
Location: Virtual
Cost: Varies; Financial aid offered
Acceptance Rate: Selective
Dates: Multiple 12-15-week cohorts throughout the year
Application Deadline: Varies by cohort. You can apply to the program here.
Eligibility: High school students. AI Fellowship applicants should either have completed the AI Scholars program or exhibit experience with AI concepts or Python.
Veritas AI, founded and run by Harvard graduate students, offers programs for high school students who are passionate about artificial intelligence. Students who are looking to get started with AI, ML, and data science would benefit from the AI Scholars program. Through this 10-session boot camp, students are introduced to the fundamentals of AI & data science and get a chance to work on real-world projects. Another option for more advanced students is the AI Fellowship with Publication & Showcase. Through this program, students get a chance to work 1:1 with mentors from top universities on a unique, individual project. A bonus of this program is that students have access to the in-house publication team to help them secure publications in high school research journals. You can also check out some examples of past projects here and read about a student’s experience in the program here.
3. MIT Beaver Works Summer Institute (BWSI)
Location: MIT Campus, Cambridge, MA, or Virtual
Cost: Free for families earning under $200,000/year
Acceptance Rate / Cohort Size: Not specified
Dates: Four-week summer programs
Application Deadline: March 30
Eligibility: Rising high school seniors who live or attend high school in the U.S.
BWSI offers more than a dozen project-based technical courses across AI, autonomous systems, cybersecurity, and satellite design, all taught by MIT faculty and Lincoln Laboratory engineers. AI-relevant tracks include CogWorks (which applies machine learning to audio, vision, and language domains), Serious Game Development with AI, Medlytics (which covers data science applied to clinical medicine), and autonomous vehicle and drone courses that combine computer vision with real hardware. An important distinguishing factor of BWSI is its multi-step admissions process, in which you must first register for and make meaningful progress in free online prerequisite coursework before becoming eligible to apply to the summer program. Your performance in those prerequisites is the primary admissions signal, and students who do not complete the minimum coursework are unlikely to advance. This makes BWSI a higher investment opportunity from the get-go, and makes even participation a prestigious add-on to your resume.
4. Lumiere Research Scholar Program - AI Track
Location: Virtual
Cost: Varies; financial assistance offered
Acceptance rate/cohort size: Selective
Dates: Sessions run throughout the year, including in the summer
Application deadline: Varies by cohort. You can apply here.
Eligibility: High school students; accepted students typically have an unweighted GPA of 3.3 out of 4.0
The Lumiere Research Scholar Program is a rigorous research program tailored for high school students. The program offers extensive 1-on-1 research opportunities for high school students across a broad range of subject areas. The program pairs high school students with Ph.D. mentors to work 1-on-1 on an independent research project. At the end of the 12-week program, you’ll have developed an independent research paper. You can choose research topics from subjects such as physics, data science, computer science, engineering, and more.
5. Columbia University DBMI Summer Research Program
Location: Columbia University Irving Medical Center, New York, NY
Cost: Free
Acceptance Rate/Cohort Size: Highly competitive; NYC-area high school students form a small share of a cohort that includes undergraduates
Dates: June 29 – August 14
Application Deadline: February 20
Eligibility: Rising high school seniors and recent high school graduates (17+) located in the NYC metropolitan area
Seven weeks at Columbia DBMI means working on an active research project led by DBMI faculty and graduate students, covering areas such as large language models in clinical settings, machine learning for disease phenotyping, mobile health applications, and algorithmic bias in medical imaging. You'll participate in weekly lab meetings that show how research is actually conducted, attend a mini-course of prerecorded faculty lectures on biomedical informatics, and present recently published papers at journal club sessions. A distinct study design component has you working with the OHDSI framework, a clinical data warehouse containing more than 800 million patient records, to propose a study of your own choosing. Past student projects include benchmarking ChatGPT-4o for clinical entity extraction, developing a mobile app for real-time Parkinson's detection through passive sensing, and detecting high-risk drug combinations linked to seizures in NewYork-Presbyterian patients.
6. Harvard T.H. Chan School of Public Health — Data Science in Action: Machine Learning for Self-Driving Cars
Location: Boston, MA, and Online
Cost: Free
Acceptance Rate: Not specified
Dates: June 29 – July 3 for the online self-paced component, followed by July 6–17 for the in-person component
Application Deadline: April 1
Eligibility: High school students with a knowledge of basic algebra
This program teaches you to train a neural network for image classification tasks and to install it in a physical toy car that navigates autonomously using your programmed model. Getting there means learning Python, implementing machine learning algorithms, including decision trees and convolutional neural networks, and applying them progressively to real classification challenges within a team. Teams work through programming exercises that move from introductory coding tasks to a final self-driving demo, with additional tutorials available via the program's YouTube channel. Lunch sessions during the in-person weeks feature machine learning researchers and data scientists from Harvard, the University of Toronto, and PayPal. The program is hosted by Harvard's Translational Data Science Center for a Learning Health System (CELEHS).
7. UCSF AI4ALL
Location: UCSF Bakar Computational Health Sciences Institute, San Francisco, CA
Cost: Free
Acceptance Rate: Not specified
Dates: June 8 – August 14
Application Deadline: March 25
Eligibility: San Francisco Unified School District (SFUSD) juniors who have taken or are currently taking AP Statistics and/or AP Computer Science
The UCSF variant of AI4ALL has you working directly on a small-group research project led by graduate students, covering AI applied to real biomedical and health research questions using data and computation. Faculty lectures cover cutting-edge applications of AI in biology and healthcare, and field trips take you to local biotech and health technology companies to see where this research leads in practice. Small-group mentoring sessions with UCSF faculty and senior researchers run alongside the project work, and career and personal development talks bring in professionals across medicine, public health, data science, and AI to help you map what this field looks like as a career. Social events with UCSF graduate students give you a direct view of academic research life from people currently living it.
8. AIMI Summer Research Internship – Stanford University
Location: Online (virtual; synchronous)
Cost: $2,400; need-based financial aid available; $45 application fee (waived for financial aid applicants)
Acceptance Rate/Cohort Size: ~50 students per session; competitive
Dates: Session A: June 15 – June 26; Session B: July 6 – July 17
Application Deadline: February 21 (standard); February 13 (financial aid)
Eligibility: U.S. residents currently attending a U.S. high school, entering grades 9–12 in the fall; ages 14+; strong math, computer programming, or biology background preferred
The AIMI Summer Research Internship is a two-week virtual program run by Stanford's Center for Artificial Intelligence in Medicine and Imaging, designed for students with a technical background in math, programming, or biology. Students are placed in small teams and paired with Stanford student leads and research mentors to work on a focused health AI project, applying concepts from lectures covering machine learning, medical imaging, clinical applications, model evaluation, and responsible AI. A guest speaker series features professionals from academia, healthcare, industry, and government sharing perspectives on real-world AI applications and career pathways. Students who complete the program receive a Certificate of Completion from Stanford AIMI and are invited to apply for the AIMI Academic Year Internship on a first-come, first-served basis.
9. MIT Jameel Clinic AI & Health Summer High School Bootcamp
Location: MIT Campus, Cambridge, MA
Cost: $2,000, though need-based financial aid and scholarships are available
Acceptance Rate: Not specified
Dates: July 13 – 17
Application Deadline: January 11 for early action, March 1 for regular
Eligibility: High school students
This one-week program digs into how machine learning is applied across healthcare, covering drug discovery, medical imaging, clinical decision support, and cardiovascular risk modeling. Instruction comes from MIT researchers and Harvard Medical School faculty whose work spans both computational and clinical contexts, including the program's AI faculty lead, a MacArthur Fellow and Distinguished Professor of AI and Health whose research covers machine learning for clinical use and natural language processing. You'll complete group work and visit neighboring organizations near the MIT campus, which brings you into contact with the infrastructure around clinical AI beyond just the classroom content. Given the program's length and the caliber of faculty involved, the depth of technical content per day is notably high.
10. Stanford AI4ALL
Location: Virtual or residential at Stanford University
Cost: $4,120 (online) | $9,800 for residential. Financial aid is available.
Acceptance rate/cohort size: Not specified
Dates: June 15 – 26 (online) | July 19 – 31 (residential)
Application Deadline: February 6
Eligibility: Current 9th-graders and rising 10th-graders aged 14 and older
At Stanford AI4ALL, you'll be placed into one of four research project groups upon admission, choosing from Computer Vision, Medical AI, Natural Language Processing, or Robotics. In Computer Vision, you'll build systems that analyze visual inputs to power applications in healthcare, agriculture, and autonomous vehicles. Medical AI work focuses on biomedical image analysis and linking visual observations to patient outcomes. In NLP, you'll learn how machines read and process language, build text classification tools, and evaluate model performance. The Robotics track puts you to work developing AI-powered systems that perceive their environment and make intelligent decisions, with applications in automation and disaster response. Past project examples include building a machine learning pipeline that uses satellite imagery to identify poverty-stricken regions in Uganda and creating an NLP classification system to analyze communications during disasters. Small-group research projects are led by Stanford graduate students and postdocs, and lectures are delivered by Stanford CS and AI faculty.
11. Georgetown University Artificial Intelligence Academy
Location: Georgetown University, Washington, D.C.
Cost: $3,095 (commuter) | $3,725 (residential)
Acceptance Rate: Not specified
Dates: June 7 – 13
Application Deadline: January 31 (early bird) | May 15 (final)
Eligibility: High school students ages 15 and older, with at least a 2.0 GPA
Georgetown's AI Academy moves through distinct, complex subject areas across the week: the science of AI from its conceptual origins to emerging frontiers, the ethics of AI, including responsible innovation, Western and non-Western ethical frameworks, and the concept of artificial moral agents, the regulation of AI across evolving global governance regimes, and the geopolitics of AI covering economics, international competition, and sustainability. You'll test AI models and work through interactive simulations to see how these systems shape decisions in real professional contexts, and guest speakers bring perspectives from industry and policy into the classroom. The program is designed by faculty from Georgetown's Applied Intelligence Program, and it closes with a capstone project where you propose your own design or policy solution within a focus area of your choosing. Off-site visits are also a part of the short but intense schedule.
12. Stanford CARE Explorers: AI x Precision Health
Location: Stanford University, Palo Alto, CA
Cost: $5,500, with limited need-based financial aid available
Acceptance Rate: Not specified
Dates: June 15 – 26 | July 6 – 17
Application Deadline: Generally in the spring, keep an eye on the website for details
Eligibility: High school students
Run by Stanford's Asian Health Research Center, this two-week program teaches you statistical data analysis techniques and AI tools for precision health data, with a specific focus on health issues affecting Asian and Asian American communities. You'll work with real health datasets, learn to recognize patterns relevant to clinical questions, and use AI methods to draw and explain meaningful findings. Instructors are field-leading researchers and clinicians in AI, medicine, and precision health. The program's tight subject focus means the technical skills you build are applied to a consistent set of substantive questions throughout, giving the AI content a clear grounding in real public health stakes rather than abstract exercises.
13. NYU Tandon Machine Learning Summer Program
Location: NYU Tandon School of Engineering, Downtown Brooklyn, NY
Cost: $3,180
Acceptance Rate: Not specified
Dates: June 15 – 27 | July 6 –17 | July 20 – 31
Application Deadline: April 17 (session 1) | May 1 (sessions 2 & 3)
Eligibility: Current high school students
Taught by Tandon faculty actively researching AI and machine learning, this two-week program covers the computer science, mathematical techniques, and data analysis methods behind image and video recognition, interactive voice systems, autonomous vehicles, real-time traffic control, and clinical diagnostics. Each session of the program has a small class roster and at least one graduate student instructor per section alongside faculty, keeping the instructional environment tight. Daily assignments run alongside a group mini-project due partway through, building your ability to apply concepts rather than just absorb them in lecture. You'll also have access to the broader New York tech landscape through organized field trips to NYC-area attractions and professional sites, and on-campus social events with other NYU summer high school students run throughout.
14. Berkeley Summer Computer Science Academy
Location: UC Berkeley Campus, Berkeley, CA
Cost: $5,197
Acceptance Rate: Not specified
Dates: June 21 – July 3
Application Deadline: March 17
Eligibility: Rising juniors and seniors aged 16+ with at least a 3.0 GPA
This two-week program moves you through the core ideas of computer science using Snap!, a visual programming language, and the core concepts of AI. The AI module covers Supervised Machine Learning, Reinforcement Learning, Generative AI, and the Ethics of AI. You'll also work through Abstraction, Boolean Logic, Algorithms, and Recursion, building toward the Code Celebration at the end of the two weeks, where you'll present an individual or group coding project to UC Berkeley CS faculty and instructors who attend to give feedback and ask questions about your work.
15. AIMI Summer Health AI Bootcamp – Stanford University
Location: Online (virtual; synchronous)
Cost: $2,000; need-based financial aid available; $45 application fee (waived for financial aid applicants)
Acceptance Rate/Cohort Size: ~50 students per session; competitive
Dates: Session A: June 15 – June 26; Session B: July 6 – July 17
Application Deadline: February 21 (standard); February 13 (financial aid)
Eligibility: U.S. residents currently attending a U.S. high school, entering grades 9–12 in the fall; ages 14+; no coding experience required
The AIMI Summer Health AI Bootcamp is a two-week virtual program run by Stanford's Center for Artificial Intelligence in Medicine and Imaging, built for students with little to no prior coding or AI experience. Lectures by Stanford researchers and clinicians cover foundational topics including machine learning basics, medical imaging, model evaluation, responsible AI, and generative AI in medicine, with structured breakout sessions and case-based exercises connecting concepts to real clinical settings. The program is designed as an entry point into health AI rather than a research experience, making it a strong option for students who want exposure to the field before committing to more technical work.
16. Harvard Computer Society (HCS) AI Summer Bootcamp
Location: Online
Cost: $795 (regular) | $995 (final priority)
Acceptance Rate: Not specified
Dates: June 1 – 5 | June 8 – 12 | June 15 – 19 | June 22–26
Application Deadline: April 28
Eligibility: High school students with strong mathematical skills, proficiency in Python, and preferably with experience in calculus
Run by Harvard undergraduates and graduate-level AI researchers, this five-day bootcamp covers the latest developments in generative AI and machine learning through lectures, coding labs, and a mini research project you develop and present during the week. Two tracks are available: the Introductory track for students comfortable with Python and mathematical reasoning but without prior AI or ML experience, and the Advanced track for those familiar with PyTorch who want to focus on independent research methodology. Both tracks draw from current AI research happening at Harvard. While shorter than most other programs on this list, its virtual format and current curriculum still make it a worthwhile option, especially if you have other commitments to balance.
17. Seth Bonder Camp in Computational and Data Science (Georgia Tech AI4OPT)
Location: Georgia Institute of Technology, Atlanta, GA or Online
Cost: Free
Acceptance Rate: Not specified
Dates: June 8 – July 10
Application Deadline: Not specified
Eligibility: High school students
Run by Georgia Tech's AI Institute for Advances in Optimization, this camp progresses through data science, machine learning, optimization fundamentals, Generative AI, and Agentic AI. The curriculum builds naturally from concept to concept across four progressive levels, and both the on-campus and online formats are offered. Partnerships with high schools in Georgia and California through the nonprofit Kids Teach Tech have expanded the program's reach to students who otherwise wouldn't encounter this level of technical AI instruction. A final symposium brings in industry guest speakers, and you'll present your project publicly at the close of the camp.
18. Tufts University — Engineering with Artificial Intelligence
Location: Tufts University, Medford/Somerville Campus, MA
Cost: $4,425 (commuter) | $5,950 (residential)
Acceptance Rate: Not specified
Dates: July 5 – 17 | July 19 – 31
Application Deadline: May 1
Eligibility: Rising sophomores through seniors or graduating seniors who have prior programming knowledge
This two-week program covers the history and societal impact of AI, hands-on implementation of machine learning tools, from low-level Python code to APIs and off-the-shelf platforms, and an overview of AI subfields, from machine learning algorithms to cutting-edge generative systems. Guest speakers from faculty and industry join each day to discuss their research and real-world AI applications. Week 2 shifts toward a culminating engineering design project in which small groups identify a real-world problem, research criteria and constraints, and then design, prototype, test, and present a technical solution at a public Project Showcase attended by friends and family. You'll leave with a personal digital portfolio documenting your work throughout the course.
19. Stanford Pre-Collegiate Summer Institutes — Artificial Intelligence
Location: Online
Cost: $3,200
Acceptance Rate: Not specified
Dates: June 15 – 26 | July 6 – 17
Application Deadline: March 13
Eligibility: Current grades 10–11 for the AI course, grades 9–11 for the Philosophy of AI course
Stanford's Summer Institutes offer two AI-focused courses in live online seminars. The Artificial Intelligence course covers supervised learning, unsupervised learning, and reinforcement learning algorithms, with attention to how bias can enter data and how to address it. You'll apply linear algebra, statistics, calculus, and optimization, and build programming proficiency by implementing algorithms in Python using both pedagogical and real-world datasets. The Philosophy of Artificial Intelligence course examines what AI actually means, whether machines can think or be conscious, and how algorithms influence decisions in banking and criminal justice. Both courses require daily synchronous attendance and include approximately 20 hours of live instruction, plus asynchronous assignments.
20. UC Berkeley BeSMART
Location: UC Berkeley Campus, Berkeley, CA
Cost: $7,000
Acceptance Rate: Highly selective, only 20 students admitted per batch
Dates: July 27 – August 7
Application Deadline: March 31
Eligibility: High school students ages 15–17
BeSMART is an inaugural residential program from UC Berkeley's Department of Industrial Engineering and Operations Research that teaches you the algorithms, data manipulation techniques, and validation methods behind modern AI through faculty-led lectures and hands-on lab sessions. You'll learn Python programming and machine learning techniques, then apply them to a final research project on a topic of personal interest using real-world datasets. Six IEOR faculty members bring expertise in data science, operations research, stochastic modeling, and applied machine learning, and the cohort cap of 20 students means you benefit from an excellent student-to-faculty ratio. The program includes visits to student laboratories and Silicon Valley companies, as well as college preparation sessions.