15 In-person Artificial Intelligence Programs for High School Students
- Stephen Turban
- 5 hours ago
- 11 min read
From healthcare and finance to education and technology, Artificial intelligence is becoming a part of most industries. If you are considering studying AI, computer science, or data science in college, participating in a program in high school can help you test that interest early. An in-person AI program may involve building simple machine learning models, analyzing datasets, or collaborating on team-based technical challenges. You will see how algorithms are implemented, how errors are corrected, and how projects evolve. That exposure helps you understand whether you enjoy what AI work requires.
Why should I participate in an in-person Artificial Intelligence program in high school?
In-person programs allow you to develop technical skills in a focused setting, with direct access to instructors and peers. The ability to ask questions immediately and receive structured guidance often deepens understanding. These experiences also provide projects and achievements to reference in college essays or interviews, especially useful if you plan to major in Computer Science.
With that, here are 15 in-person Artificial Intelligence programs for high school students!
Location: Carnegie Mellon University, Pittsburgh, PA
Cost: Fully funded (tuition, housing, meals, and select field trips covered; limited travel assistance available)
Acceptance rate/cohort size: Highly selective; cohort size not publicly disclosed
Dates: June 20–July 18 (4 weeks)
Application Deadline: February 1
Eligibility: Rising high school seniors (between 11th and 12th grade); must be at least 16 years old by program start; U.S. citizens or permanent residents
AI Scholars is a fully funded, merit-based summer program that allows you to study artificial intelligence in an immersive, college-level environment at Carnegie Mellon University. During the four-week residential program, you will take part in classroom instruction, faculty-led lectures, and research and group projects focused on AI challenges. The curriculum emphasizes project-based learning and culminates in a final symposium where you present your work to peers and mentors. In addition to technical instruction, you participate in weekly college-preparation seminars on admissions, financial aid, and personal development. You also gain exposure to industry perspectives through guest speakers and organized experiences while receiving mentorship from CMU faculty and researchers.
Location: Oxford, Cambridge, Singapore, Sydney, Toronto, and Boston
Cost: Varies by location and cohort; financial aid available
Acceptance rate/cohort size: Small-group instruction, typically 7–10 students
Dates: 2 weeks during the summer (multiple cohorts)
Application Deadline: Rolling admissions (varies by cohort)
Eligibility: Students aged 13–18 currently enrolled in middle or high school
Immerse Education’s Artificial Intelligence Track allows you to experience university-style learning while living on campus at leading academic hubs around the world. You study in small seminar-style groups and learn from tutors affiliated with institutions such as Oxford and Cambridge, with an emphasis on discussion-based and applied learning. The AI track introduces core concepts in artificial intelligence while encouraging you to think critically about how these technologies are designed and used in real-world contexts. Coursework is experiential, often incorporating hands-on activities, problem-solving exercises, and collaborative projects with peers from diverse backgrounds. By the end of the program, you will complete a personal project and receive detailed written feedback along with a certificate of completion.
Location: Princeton University, Princeton, NJ
Cost: Free (fully funded)
Acceptance rate/cohort size: Highly selective; cohort size not publicly disclosed
Dates: July 9–July 30
Application Deadline: April 9
Eligibility: Low-income high school students in the U.S. or Puerto Rico
Princeton AI4ALL is a fully funded, residential summer program that introduces you to artificial intelligence through the lens of social impact and interdisciplinary problem-solving. Hosted by Princeton’s Computer Science Department in partnership with the AI4ALL organization, the program combines lectures, hands-on projects, and mentorship from faculty, graduate students, and researchers. You will work in teams on AI projects in areas such as biodiversity, medicine, natural language processing, and AI governance, using data to address challenges. The curriculum emphasizes both technical foundations and ethical considerations, helping you understand how AI systems can reflect or reinforce societal biases. You also participate in discussions, presentations, and field-trip-style learning experiences that connect AI to policy and public interest.
Location: Georgia Institute of Technology, Atlanta, GA, and partner sites in Georgia and California (in person; some hybrid/online components through partners)
Cost: Free (NSF-funded programs)
Acceptance rate/cohort size: Selective; varies by program and partner site
Dates: Summer programs and academic-year courses (timelines vary by initiative)
Application Deadline: Varies by program and host site
Eligibility: High school students
The NSF AI Research Institute for Advances in Optimization (AI4OPT) offers a range of in-person and hybrid programs designed to introduce you to artificial intelligence and machine learning at an early stage. Through high school courses, summer camps, and internships, you gain hands-on exposure to AI concepts with a strong emphasis on deep learning and computer vision. Programs such as the Seth Bonder Summer Camps provide tiered instruction, progressing from introductory programming and data science to building deep learning, generative, and agentic AI models. You also have opportunities to participate in AI-focused internships, collaborating with researchers and contributing to real-world projects under expert mentorship. Many initiatives are delivered in partnership with high schools, including Drew Charter High School in Atlanta, where students engage in machine–learning–based engineering practice courses using tools such as Python.
Location: University of Washington, Seattle, WA
Cost: Free
Acceptance rate/cohort size: Selective; small-cohort, small-forum instruction
Dates: 20-week program (timelines vary by cohort)
Application Deadline: Not publicly specified
Eligibility: Rising high school juniors, high school seniors, and college freshmen
AI4ALL | UW is a free, extended data science and machine learning program hosted by the University of Washington’s Taskar Center for Accessible Technology. The program introduces you to foundational concepts in data science and machine learning, with an emphasis on understanding how these tools are used in decision-making. Instruction takes place in small-group settings, allowing you to analyze datasets, discuss applications, and practice technical concepts in a collaborative environment. A distinguishing feature of the program is its focus on anti-bias and non-ableist approaches to data science, drawing from disability studies to critically examine fairness and accessibility in technology.
Location: Georgetown University, Washington, DC
Cost: $3,725 residential; $3,095 commuter
Acceptance rate/cohort size: Selective
Dates: June 7–June 13
Application Deadline: Rolling admissions (closes when capacity is reached)
Eligibility: High school students (typically grades 9–12)
The Artificial Intelligence Academy at Georgetown University allows you to explore AI through an interdisciplinary lens that combines technical foundations with ethics, regulation, and global policy. You will participate in lectures, guest talks, guided discussions, and activities that introduce how AI systems function and how they are used across industry and government. Throughout the program, you work with real-world case studies, test simple AI models, and engage in applied projects that examine both the capabilities and limitations of current technologies. The curriculum emphasizes responsible AI, including topics such as bias, transparency, accountability, and international governance frameworks.
Location: Brown University, Providence, RI
Cost: Tuition-based; additional requirement of up to $50 in OpenAI credits. Check details here.
Acceptance rate/cohort size: Not publicly disclosed
Dates: July 6–July 24
Application Deadline: Varies, check here.
Eligibility: High school students with a minimum prerequisite of basic algebra
Decision Making & Problem Solving with Multi-Agent AI Systems introduces you to applied artificial intelligence with a focus on agentic and multi-agent architectures. You will study the evolution of AI, generative models, and large language models before moving on to work with AI agents that can take actions and interact with systems. The course emphasizes practical applications, allowing you to design and build simple agentic systems and map AI-driven solutions to real-world problems in areas of personal interest. Through guided exercises, you explore concepts such as LLM chains, autonomous agents, and collaborative multi-agent systems.
Location: NYU Tandon School of Engineering, Brooklyn, NY
Cost: Tuition-based (cost varies based on partnership package)
Acceptance rate/cohort size: Not publicly disclosed
Dates: 2-week summer program (next session dates to be announced)
Application Deadline: Not yet announced
Eligibility: Students aged 15+ (current 9th grade through graduating 12th grade)
IDEA is a summer program that introduces you to artificial intelligence through the lens of entrepreneurship, innovation, and public service. The curriculum combines foundational AI concepts with business case studies and research projects that examine how AI can improve products and services in public-facing industries. You will explore the theoretical grounding of artificial intelligence while analyzing gaps and opportunities for innovation across contemporary organizations. The program emphasizes project-based learning, guiding you from ideation to implementation as you work in teams to design AI-powered solutions. You also develop entrepreneurial thinking skills, learning how technical ideas translate into viable, impact-driven initiatives.
Location: NYU Tandon School of Engineering, Brooklyn, NY
Cost: $3,180 total; housing and meals available at additional cost
Acceptance rate/cohort size: Selective
Dates: June 15–June 27, July 6–July 17, or July 20–July 31
Application Deadline: Session 1: April 17; Sessions 2 & 3: May 1
Eligibility: Students aged 15+ (current 9th grade through graduating 12th grade); open to U.S. residents and international students; prerequisites include precalculus and programming experience
The Machine Learning Summer Program at NYU Tandon introduces you to the core principles that power modern AI and data-driven technologies. Through programming and guided instruction, you will learn how machine learning models are built, trained, and evaluated using datasets. The curriculum covers foundational topics such as data analysis, neural networks, model validation, and mathematical techniques underlying machine learning systems. You apply these concepts to real-world use cases, including image and video recognition, autonomous systems, voice-based technologies, and medical diagnostics.
Location: New York City, NY (in person; live online and self-paced options available)
Cost: $2,195 full tuition after discount
Acceptance rate/cohort size: Small class sizes
Dates: June 29–July 17, July 20–July 30, or August 3–August 13 (multiple session formats)
Application Deadline: Rolling admissions (start anytime for self-paced option)
Eligibility: High school students
The Python Data Science & AI Machine Learning Program introduces you to Python programming with a focus on data science and applied machine learning. Through live, project-based instruction, you will learn Python fundamentals before moving into data analysis using libraries such as Pandas, Matplotlib, and scikit-learn. You will work with real datasets, build visualizations, and apply machine learning concepts to practical problems. Instruction is delivered by industry-experienced instructors, with opportunities for one-on-one support and access to class recordings. You complete projects that reinforce core concepts and receive a verified digital certificate upon completion.
Location: Massachusetts Institute of Technology, Cambridge, MA (in person; non-residential)
Cost: $2,000; scholarships available
Acceptance rate/cohort size: Highly selective; cohort size not publicly disclosed
Dates: 1 week during the summer
Application Deadline: Early Action: January 11; Regular: March 1
Eligibility: High school students in grades 10–12; incoming sophomores, juniors, and seniors
The MIT Jameel Clinic AI & Health Summer High School Bootcamp is a rigorous, one-week program that introduces you to how artificial intelligence and machine learning are transforming healthcare and biomedical research. Hosted on MIT’s campus, the program combines lectures, hands-on instruction, and group-based projects led by world-class faculty, clinicians, and researchers. You will explore topics such as machine learning in health, clinical AI, drug discovery, and Python programming, with coursework designed to balance theory and application. Throughout the week, you work collaboratively on group projects that culminate in a final presentation evaluated by instructors. Instruction emphasizes ethical deployment, precision medicine, and the role of AI in accelerating scientific discovery.
Location: University of Washington, Seattle, WA (online option also available)
Cost: $895; nonrefundable $50 registration fee per quarter
Acceptance rate/cohort size: Not publicly disclosed
Dates: March 31–May 28 (online) or June 29–July 10 (in person; multiple daily sessions)
Application Deadline: Rolling registration until sessions fill
Eligibility: Students in grades 9–12; foundational Python knowledge required
Introduction to AI & Machine Learning at the University of Washington introduces you to the core ideas behind artificial intelligence and how these technologies are used in everyday applications. You will study foundational topics such as machine learning, neural networks, computer vision, reinforcement learning, and generative AI, including large language models. The course emphasizes applied learning, guiding you through building your own AI tool while learning how to evaluate and use AI systems effectively. You also examine ethical considerations related to responsible AI development and real-world deployment. Upon completion, you earn a digital badge that can be highlighted on college and job applications.
Location: Wake Forest University Reynolda Campus, Winston-Salem, NC
Cost: $3,500
Acceptance rate/cohort size: Not publicly disclosed
Dates: Week of June 7–12 or week of June 21–26
Application Deadline: Applications open November 1
Eligibility: Current high school students in grades 9–12
The Artificial Intelligence Institute at Wake Forest University offers you an immersive, residential introduction to AI and its role in shaping technology, society, and global systems. Through a combination of workshops, guest lectures, and projects, you will explore core AI concepts such as machine learning, natural language processing, and robotics. The program places strong emphasis on ethical and societal dimensions, including bias, transparency, privacy, and global AI governance. You collaborate with peers on AI-driven projects ranging from chatbot development to data analysis, while also participating in simulations and debates around real-world ethical dilemmas. Upon completion, you receive an official Wake Forest University Certificate of Completion.
Location: University of Virginia (Inspire Program), Fairfax, VA
Cost: $2,000 early-bird pricing; subject to increase after March 1
Acceptance rate/cohort size: Not publicly disclosed
Dates: July 27–July 31
Application Deadline: Rolling admissions
Eligibility: High school students; no prior programming experience required
The AI Literacy Bootcamp at the University of Virginia is an intensive, one-week program designed to help you understand how artificial intelligence systems work and how they impact society. Through interactive lectures, labs, and collaborative activities, you will explore core concepts such as machine learning, deep learning, computer vision, natural language processing, and generative AI. Using beginner-friendly, no-code platforms, you build and test your own AI models while learning skills like prompt engineering and model evaluation. The curriculum places strong emphasis on ethical considerations, including bias, privacy, fairness, and the societal implications of AI adoption. You also examine real-world applications of AI across industries such as healthcare, entertainment, and technology, gaining insight into potential career pathways.
Location: Brown University, Providence, RI
Cost: Tuition-based; additional requirement of up to $50 in OpenAI credits. Check details here.
Acceptance rate/cohort size: Not publicly disclosed
Dates: June 29–July 10
Application Deadline: Varies, check the website for the latest deadlines
Eligibility: High school students
From Curiosity to Insight: AI-Driven Biomedical Discovery for Precision Medicine introduces you to how artificial intelligence and data science are used to address real-world challenges in healthcare and life sciences. You will study core concepts in biomedical data science, including biostatistics, computational biology, and AI-driven analysis techniques. You explore applied topics such as cancer genomics, personalized medicine, and clinical diagnostic automation, learning how to identify patterns and generate insights from real biomedical datasets. You develop skills in hypothesis formation, data visualization, and scientific communication, culminating in research presentations and a draft scientific manuscript.
One other option—the Lumiere Research Scholar Program
If you’re interested in pursuing independent research, consider applying to one of the Lumiere Research Scholar Programs, selective online high school programs for students founded with researchers at Harvard and Oxford. Last year, we had over 4,000 students apply for 500 spots in the program! You can find the application form here, check out students’ reviews of the program here and here.
Also check out the Lumiere Research Inclusion Foundation, a non-profit research program for talented, low-income students. Last year, we had 150 students on full need-based financial aid!
Stephen is one of the founders of Lumiere and a graduate of Harvard College, where he earned an A.B. in Statistics. He founded Lumiere as a PhD student at Harvard Business School. Lumiere is a selective research program where students work 1-1 with a research mentor to develop an independent research paper.
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