As a high school student, learning about artificial intelligence gives you early exposure to a field that is increasingly central to technology, science, and industry. AI programs help you build foundational skills in areas such as machine learning, data analysis, algorithmic thinking, and ethical decision-making, while also strengthening your broader STEM profile. These experiences allow you to move beyond classroom theory and apply concepts through structured projects, coding exercises, and real-world problem solving.
Why Free AI Programs Are Valuable
Free AI programs make high-quality learning opportunities accessible without financial barriers, allowing you to explore advanced topics without committing significant resources. Many of these programs are hosted by universities, research institutions, or established organizations and offer rigorous curricula, mentorship, and hands-on work at no cost. Even without tuition fees, they often mirror the academic expectations and technical workflows used in college-level or professional AI settings.
To help you identify meaningful options, we’ve curated 15 free artificial intelligence programs for high school students that stand out for their rigor, learning outcomes, and opportunities to engage with experienced instructors or mentors.
If you’re interested in coding, check out this blog on free fall coding programs.
1. National Institute of Standards and Technology (NIST) Internships
Location: NIST labs in Boulder, CO, or Gaithersburg, MD
Cost/Stipend: None
Acceptance Rate: Competitive
Dates: June 22 – August 7
Application Deadline: January 26
Eligibility: Juniors or seniors in high school with a minimum GPA of 3.0; Applicants must live within a 50-mile radius of their host campus
The NIST Summer High School Internship Program places you in active research labs alongside NIST scientists and engineers. If you’re interested in artificial intelligence, you’ll get to work within the Information Technology Laboratory (ITL), where research focuses on AI, machine learning, data mining, biometrics, cryptography, and computer security. During the internship, you’ll contribute to real research projects involving tasks such as image analysis, software testing, information visualization, and statistical modeling. The program emphasizes applied research, exposing you to how AI systems are evaluated, measured, and standardized for real-world use. This experience provides early insight into government-led AI research and how computational science supports national technology and security standards.
2. Air Force Research Laboratory (AFRL) Scholars Program
Location: Several locations across the U.S.
Cost/Stipend: No cost; Stipends are paid based on the educational level (see rates here)
Acceptance Rate: Highly selective
Dates: Varies based on opportunity
Application Deadline: January 10
Eligibility: U.S. upper-level high school students (16+) with a grade point average of at least 3.0 on a 4.0 scale; More details here
The AFRL Scholars Program is a paid summer research internship for high school students interested in engineering, technology, and applied research. As a participant, you’ll work directly with Air Force Research Laboratory scientists and engineers on active research projects, gaining exposure to professional research environments. While AFRL’s core focus is aerospace and defense technology, select projects integrate artificial intelligence, machine learning, data analysis, and computational modeling. You will contribute to real-world research challenges while learning how AI tools are applied in large-scale engineering and defense systems. The program emphasizes mentorship, hands-on learning, and practical experience in advanced research labs.
3. NYU’s Applied Research Innovations in Science and Engineering (ARISE)
Location: NYU Tandon School of Engineering, Brooklyn, NY
Cost/Stipend: No cost; $1,000
Acceptance Rate: Highly selective
Dates: June 1 – August 14
Application Deadline: January 15 – February 20
Eligibility: Students who are completing 10th or 11th grade in June and living in New York City
NYU ARISE is a highly selective, seven-week paid summer research program for high school students interested in science, engineering, and artificial intelligence. The program begins with two weeks of intensive workshops covering research ethics, data analysis, coding foundations, and scientific communication. You’ll then spend five weeks working in NYU faculty-led research labs, collaborating closely with professors, graduate students, and postdoctoral researchers. AI-focused labs include Machine Learning for Good, Automation and Intelligence for Civil Engineering, and applied machine learning labs that work on real-world problems such as healthcare access, infrastructure systems, and social impact analytics. Throughout the program, you’ll gain hands-on experience with data-driven research, model development, and ethical considerations in AI. The experience concludes with a formal research presentation at a final colloquium, where you’ll share your findings in a professional academic setting.
4. Anson L. Clark Scholars Program at Texas Tech University
Location: Texas Tech University campus, Lubbock, TX
Cost/Stipend: $25 application fee; $750
Cohort Size: 12 students
Dates: June 21 – August 6
Application Deadline: February 16
Eligibility: High school students (17+) who are about to graduate
The Anson L. Clark Scholars Program is a highly selective, seven-week paid research experience for high school students interested in advanced academic research. As a participant, you’ll conduct independent research under the close mentorship of a Texas Tech faculty member in a field of your choice. While the program is interdisciplinary, you can incorporate artificial intelligence, machine learning, data science, or computational methods into areas such as computer science, engineering, or applied mathematics. Research topics may include big data analysis, robotics, simulation, or AI-driven systems, depending on faculty availability. The program emphasizes research design, independent inquiry, and scholarly communication at a level similar to early undergraduate research.
5. Carnegie Mellon’s AI Scholars
Location: Carnegie Mellon University, Pittsburgh, PA
Cost/Stipend: None
Acceptance Rate: Highly selective
Dates: June 20 – July 18
Application Deadline: February 1
Eligibility: 11th-grade students (16+) at the time of application; U.S. citizen or permanent resident with a current U.S. green card
Carnegie Mellon’s AI Scholars is a fully funded, four-week residential summer program for rising high school seniors interested in artificial intelligence and computer science. During the program, you’ll study core AI and computing concepts through college-level coursework taught by CMU faculty, with a strong emphasis on hands-on, project-based learning. Before arriving on campus, you’ll complete a required virtual Python course that builds foundational coding skills, making the program accessible even if you’re new to programming. You’ll work in teams on applied AI projects, gain exposure to CMU research labs, and explore how AI is used in real-world academic and industry settings. The experience culminates in a capstone symposium where you will present your work, alongside college preparation seminars and mentorship that support your academic and career goals.
6. UT Computer Science Summer Academy for All
Location: UT Austin, Austin, TX
Cost/Stipend: None
Acceptance Rate: Selective
Dates: June 7 – 13 (Standard); June 14 – 19 (ML)
Application Deadline: December 22
Eligibility: Students entering 11-12 grade in the fall
UT Austin’s Computer Science Summer Academy for All is a week-long residential program that introduces you to core computer science concepts through hands-on, team-based projects. You can choose between the Standard Edition, where you’ll work with C++ and Arduino microcontrollers to build hardware-driven systems, or the Machine Learning Edition, which focuses on Python and foundational machine learning techniques. In the Machine Learning track, you’ll apply AI concepts such as data preprocessing, model training, and evaluation to understand how algorithms are used in areas like pattern recognition and automated decision-making. Faculty-led workshops connect these technical skills to real-world AI applications while also addressing ethical and societal considerations of machine learning. Beyond coding, the program offers exposure to tech career pathways, UT admissions guidance, and a full campus-life experience through residential living and collaboration with current UT students.
7. Princeton University’s AI4ALL Program
Location: Princeton University, Princeton, NJ
Cost/Stipend: None
Acceptance Rate: Selective
Dates: July 9 – July 30 (tentative)
Application Deadline: April 9 (tentative)
Eligibility: Rising 11th-grade students who live in the United States and Puerto Rico and who qualify as low-income
Princeton’s AI4ALL Program is a three-week summer program that introduces you to the technical foundations of artificial intelligence alongside its ethical and social implications. You’ll learn how AI systems are built through hands-on labs covering topics like machine learning models, data representation, and algorithmic decision-making. Through guided projects, you’ll apply AI to real-world use cases such as analyzing social data, understanding pattern recognition, or evaluating how algorithms impact fairness and bias. Daily lectures from Princeton faculty connect theory to active research areas, helping you see how AI is used in academic and applied settings. The program emphasizes responsible AI development, encouraging you to critically examine how AI affects society, policy, and human decision-making.
8. Science and Engineering Apprenticeship Program (SEAP)
Location: Multiple lab locations across the country
Cost/Stipend: No cost; Stipend of $4,000 for new participants, $4,500 for returning participants
Acceptance Rate: Highly selective
Dates: 8 weeks during the summer, with the option to extend for up to two more weeks
Application Deadline: August 1 – November 1
Eligibility: High school students who have completed at least 9th grade (16+) and are U.S. citizens; Check the specific lab’s additional requirements or exceptions
The Science and Engineering Apprenticeship Program (SEAP) is an eight-week summer research internship that places you inside one of many U.S. Department of the Navy laboratories. You’ll work directly with Navy scientists and engineers on active research projects in areas such as computer science, applied mathematics, robotics, and engineering. Many placements involve artificial intelligence applications, including machine learning experiments, data modeling, cybersecurity analysis, autonomous systems, or AI-supported decision tools, depending on the lab. Throughout the program, you’ll gain hands-on experience with research workflows, technical problem-solving, and real-world data in a federal research environment. SEAP also offers structured mentorship and exposure to STEM career pathways in government, defense, and advanced technology research.
9. MIT Beaver Works Summer Institute
Location: MIT, Cambridge, MA, or virtual
Cost: Free for qualifying families; Check details here
Acceptance Rate: Highly selective
Dates: Varies by course
Application Deadline: Varies by course
Eligibility: U.S. high school students who are no higher than juniors
The MIT Beaver Works Summer Institute (BWSI) is a highly selective, fully funded summer program run by MIT Lincoln Laboratory that immerses you in hands-on work with AI, machine learning, robotics, and cybersecurity. You’ll take part in project-based courses where AI is applied to real-world challenges such as autonomous vehicles, intelligent assistants, game simulations, and computer vision systems. Tracks like CogWorks and Serious Games with an AI focus on training and testing models using Python while exploring how AI systems behave in realistic environments. The program emphasizes teamwork, problem-solving, and ethical thinking alongside technical skill development. By the end of the program, you’ll gain direct exposure to how advanced AI research is designed and implemented in real engineering contexts.
10. UCSD Research Experience for High School Students
Location: UCSD, La Jolla, CA
Cost: Free for non-research projects; $1,500 for research
Acceptance Rate: Selective
Dates: June 8 – July 31
Application Deadline: March 15
Eligibility: Southern California high school students (16+) who are in grades 10-12 with a minimum cumulative grade point average of 3.0
The UCSD Research Experience for High School Students, hosted by the San Diego Supercomputer Center (SDSC), is an eight-week summer program where you’ll work with faculty mentors on real computational research projects. Depending on the project, you may apply machine learning, data analytics, bioinformatics, or large-scale computing to analyze complex datasets and test research hypotheses. You’ll learn how computational tools and AI-driven methods are used in scientific discovery, while also gaining experience with research workflows such as lab meetings, experimentation, and data interpretation. The program includes training in scientific communication, helping you present your findings through posters at the end-of-summer showcase.
11. MITES Summer
Location: MIT, Cambridge, MA
Cost/Stipend: None
Acceptance Rate/Cohort Size: Highly selective; 60-80 students
Dates: 6 weeks over the summer from late June through early August
Application Deadline: February 1
Eligibility: High school juniors who are U.S. citizens or permanent residents
MITES Summer is a fully funded, six-week residential program at MIT that immerses you in rigorous, college-level STEM coursework. You’ll take five intensive core classes in math, science, and humanities, along with electives in advanced areas such as machine learning, genomics, and data-driven problem solving. Through fast-paced lectures, problem sets, and team-based projects, you’ll develop strong analytical and computational thinking skills while applying concepts similar to those used in AI and quantitative research. The program also includes lab tours, seminars with STEM professionals, and exposure to how fields like machine learning are used in real-world research and industry.
12. AI4ALL@UW
Location: Online
Cost/Stipend: None
Acceptance Rate: Selective
Dates: 20 weeks (Fall: September 8 – January 26)
Application Deadline: July 31 (fall)
Eligibility: Rising high school juniors, high school seniors, or students starting their freshman year of college
AI4ALL@UW is a free, 20-week introductory program in data science and machine learning offered by the University of Washington’s Taskar Center for Accessible Technology. You’ll learn core concepts in data analysis, modeling, and machine learning while examining how AI systems impact real people and communities. A key focus of the program is understanding bias, fairness, and accessibility in technology, using a disability studies lens to evaluate AI decision-making. Through small-group discussions and hands-on activities, you’ll practice interpreting data, analyzing models, and discussing ethical trade-offs in real-world applications. Taught by UW faculty and researchers, the program emphasizes responsible AI development and helps you build both technical foundations and critical thinking skills around technology’s social impact.
13. AIMI Summer Research Internship
Location: Online
Cost: $2,400 + $45 application fee; Full financial aid available
Cohort Size: 50 students
Dates: Session 1: June 15 – 26, Session 2: July 6 – 17
Application Deadline: February 20
Eligibility: U.S. high school students (14+) entering grade 9-12 in the fall
The Stanford AIMI Summer Research Internship is a two-week virtual program that introduces you to the application of artificial intelligence in medicine and healthcare. Hosted by the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), the program focuses on how machine learning models are developed, evaluated, and applied to real clinical problems. You’ll attend technical lectures on AI fundamentals, medical imaging, and healthcare data, and participate in guided group research projects using real-world medical datasets. Throughout the program, Stanford researchers and student leads provide mentorship, helping you understand both the technical and clinical considerations behind AI-driven healthcare solutions. In addition to research sessions, you’ll join expert talks and career discussions that explore pathways in medical AI, biomedical engineering, and data science. Once you complete the program, you’ll receive a Certificate of Completion.
14. AIMI Academic Year Research Internship
Location: Online
Cost: $4,800; Full financial aid available
Cohort Size: Small cohort sizes
Dates: September 29 – June 5
Application Deadline: Rolling (first-come, first-served)
Eligibility: U.S. high school students (14+) entering grades 9-12 in the fall; More details here
The AIMI Academic Year Research Internship is a virtual, extended research program for high school students seeking deeper engagement in health AI beyond summer programs. You’ll work in small teams on semester-long projects guided by Stanford mentors, contributing to technical or non-technical research in AI for healthcare. Technical projects may involve literature reviews, exploratory data analysis, model development, or scientific writing, while non-technical projects focus on ethics, bias, policy, and responsible AI implementation. The program requires significant independent work outside mentorship sessions, mirroring real research environments. You will present your work during Stanford Health AI Week and gain exposure to academic publishing, conferences, and professional research communication.
15. HarvardX: CS50’s Introduction to Artificial Intelligence with Python
Location: Online
Cost/Stipend: Free to audit
Acceptance Rate/Cohort Size: Not specified
Dates: 7 weeks; Self-paced
Application Deadline: Available year-round
Eligibility: All learners, including high school students
HarvardX: CS50’s Introduction to Artificial Intelligence with Python is a rigorous, college-level online course that introduces you to the foundations of modern AI through hands-on Python programming. You’ll learn how core AI systems work by implementing algorithms for search, optimization, machine learning, neural networks, natural language processing, and reasoning. Rather than focusing on theory alone, the course emphasizes practical application through structured coding projects that mirror real AI use cases like game-playing engines, handwriting recognition, and machine translation. You’ll gain experience working with AI concepts such as classification, large language models, and constraint satisfaction while building functional programs from scratch.
One more option – Horizon Academic Research Program
If you’re looking for a competitive mentored research program, consider applying to Horizon’s Research Seminars and Labs! This is a selective virtual research program that lets you engage in advanced research and develop a research paper on a subject of your choosing. Horizon has worked with 1000+ high school students so far and offers 600+ research specializations for you to choose from. You can find the application link here!
Image Source – Carnegie Mellon University