12 AI Winter Programs for High School Students
If you’re a high school student interested in artificial intelligence, winter programs are a great way to explore the field over a shorter, more flexible period of time. Winter programs can help you build technical skills, gain exposure to real-world applications, and even connect with mentors and professionals in the area. These programs usually allow you to avoid the longer commitment often associated with summer programs and utilize your break to learn and add to your resume.
Many of these AI programs are offered by prestigious universities, organizations, research institutes, and industry leaders. They provide you with the chance to work on projects, learn coding and data analysis, and explore how AI is applied in areas like healthcare, finance, robotics, and environmental science. Along the way, you’ll also develop valuable skills like critical thinking, technical writing, problem-solving, collaboration, and scientific presentation. No matter your level of experience, these programs provide a structured way for you to dive deeper into AI and discover how it’s shaping the world around you.
To help you get started, here is a list of 12 AI winter programs for high school students.
1. Sandia National Laboratories Internships
Location: Virtual or in person at Sandia National Laboratories, Albuquerque, NM, or Livermore, CA
Cost/Stipend: Free | This is a paid internship, with rates varying based on location, internship, and education level. Click here for the intern pay rate chart
Acceptance Rate/Cohort Size: Varies depending on the internship and Sandia’s workforce needs
Program Dates: Internships are available year-round
Application Deadline: Apply at least 3 months before your preferred internship’s start date
Eligibility: U.S. students who are at least 16 years old | Minimum cumulative GPA for high school students applying for Research and Development (R&D) or Technical positions is 3.0/4.0 | Minimum cumulative GPA for high school students applying for clerical or laborer positions is 2.5/4.0
At Sandia National Laboratories, you can participate in internships that expose you to research in engineering, computer science, and related technical fields. As an intern, you’ll work alongside mentors on real-world projects that may involve topics such as aerospace systems, remote sensing, or advanced data analysis. Some projects may also involve AI-related applications, such as developing algorithms for data processing or testing predictive models. You’ll gain experience in teamwork, research methods, and technical communication, while also participating in seminars, workshops, and site activities that provide a broader view of Sandia’s national security mission. Internships are available at Sandia’s New Mexico and California sites, with schedules designed to balance academic commitments and hands-on research. Mentorship from Sandia scientists and engineers is a central component of the experience, ensuring you develop both technical knowledge and professional skills.
2. Veritas AI
Location: Virtual
Cost: Costs vary by program type; Financial aid available
Acceptance Rate/Cohort Size: Selective
Program Dates: Multiple cohorts throughout the year, including winter (check here for Winter Cohort dates)
Application Deadline: On a rolling basis. Spring (January), Summer (May), Fall (September), and Winter (October/November). You can apply to the program here.
Eligibility: High school students from across the globe | AI Fellowship applicants should either have completed the AI Scholars program or possess a basic understanding of Python
Veritas AI gives high school students the chance to learn about artificial intelligence through both lectures and hands-on projects. In the AI Scholars program, you’ll take part in a 10-session boot camp that introduces you to the foundations of AI, machine learning, and data science, with opportunities to apply what you’ve learned to practical group projects. If you already have experience in the field, the AI Fellowship with Publication & Showcase program allows you to work one-on-one with AI mentors from leading universities on an original project. You will also receive support from a publication specialist to refine your research for submission to academic journals. Through these opportunities, you’ll explore how AI connects to fields like healthcare, finance, sports, and the environment. You can check out some of our past student projects here!
3. Research Opportunities at Cleveland Clinic Lerner Research Institute
Location: Cleveland Clinic Lerner Research Institute, Cleveland, OH
Cost/Stipend: None
Acceptance Rate/Cohort Size: Varies based on the lab
Program Dates: Research opportunities are available year-round; exact dates depend on the lab, availability, and the Principal Investigator
Application Deadline: Rolling, based on lab availability
Eligibility: High school students aged 16 and older
At the Cleveland Clinic Lerner Research Institute, you have the chance to explore careers in biomedical research by working in one of the Institute’s laboratories. First, identify labs that align with your interests and contact the Principal Investigator directly to discuss possible opportunities. If accepted, you’ll gain hands-on experience with lab techniques and exposure to the process of conducting professional research. Students interested in AI-related biomedical research can explore the Quantitative Health Sciences department, where projects might involve developing prediction models for medical decision-making, applying machine learning to medical imaging, or using AI in healthcare informatics. Please note that not all labs accept high school students, so you may need to contact multiple faculty members to find a suitable placement. Click here to learn more about the application process.
4. Lumiere Research Scholar Program – AI Tracks
Location: Virtual
Cost: Varies by program type; Financial aid available
Acceptance Rate/Cohort Size: Selective
Program Dates: 12 weeks to 12 months starting from December 8 (Winter Cohort) or January 19 (Winter Cohort II)
Application Deadline: Varying deadlines based on cohort.
Eligibility: High school students who demonstrate a high level of academic achievement
In the Lumiere Research Scholar Program, you’ll work closely with a Ph.D. mentor for over 12 weeks to 12 months, as you design and carry out an independent research project. You’ll have the opportunity to explore topics across a wide range of fields, including artificial intelligence, machine learning, data science, psychology, physics, economics, computer science, and more. Throughout the program, you’ll gain experience in reading and analyzing scholarly articles, refining research questions, and developing the skills needed to conduct academic-level investigations. The program emphasizes one-on-one mentorship, allowing you to delve deeply into your chosen subject while developing critical thinking, writing, and presentation skills. Your experience will culminate in the completion of an original research paper that you will present at the Lumiere Research Symposium. Students participating in the Premium Research & Publication Program will get additional support from a publication expert in preparing their paper for submission to scientific journals.
5. Johns Hopkins Applied Physics Laboratory’s (APL) ASPIRE Program
Location: In-person at Johns Hopkins APL, Laurel, MD (virtual opportunities are also available)
Cost/Stipend: None
Acceptance Rate/Cohort Size: 10% acceptance rate
Program Dates: June 24 – August 21 (Summer internship); can be extended into the academic year (September – May)
Application Deadline: January 1 – February 15
Eligibility: U.S. high school juniors or seniors who are at least 15 years old | Minimum GPA of 2.8 | Permanent residence in one of the following Maryland counties: Anne Arundel, Baltimore (County or City), Calvert, Carroll, Charles, Frederick, Howard, Montgomery, Prince George’s; one of the following Virginia counties/cities: Alexandria, Arlington, or Fairfax; or the District of Columbia (students in Calvert or Charles Counties are only eligible for virtual ASPIRE internship placements)
In the Johns Hopkins APL’s ASPIRE Program, you’ll work alongside APL staff mentors on hands-on projects that expose you to real STEM careers before college. You can choose placement areas such as Artificial Intelligence and Machine Learning, where past projects have involved testing AI models for cybersecurity, developing deep-learning techniques for drone detection, or evaluating the risks of generative AI disinformation. While ASPIRE is primarily a summer program, you may decide with your mentor to extend your internship through the academic year into the fall, winter, and beyond, allowing you to continue building research skills over an extended period. As an academic year intern, you’ll commit to 80–130 hours depending on your grade level, with opportunities to work either in person at APL or remotely. The program emphasizes collaboration, persistence, and independent problem-solving. All students conclude their internship by submitting a digital poster of their project at the end of May.
6. Generation AI @ MIT
Location: Online, hybrid, or in-person at various schools, organizations, or the MIT campus. Inquire here to learn about the nearest active programs
Cost/Stipend: None
Acceptance Rate/Cohort Size: Not specified
Program Dates: Year-round, including in the winter
Application Deadline: Varies, depending on the school or organization hosting the programs
Eligibility: High school students aged 14–18
Generation AI @ MIT collaborates with schools and organizations worldwide to offer one- to two-week-long AI-focused programs for high school students. As a participant, you’ll gain hands-on experience in developing AI-powered mobile applications and solutions to real-world challenges, while also exploring a range of AI concepts, ethics, and entrepreneurship opportunities. Through a series of fun challenges, the program emphasizes responsible design aspects, allowing you to think critically about AI’s potential, risks, and its ability to transform entire industries. The experience culminates in a capstone project, where you will collaborate in teams and apply what you’ve learned to build an AI solution for a problem of your choice. You will present this project at a competition or showcase, highlighting your technical expertise and problem-solving skills. You will also receive a certificate of completion upon completing the program.
7. Aspiring Scholars Directed Research Program (ASDRP)
Location: ASDRP Labs in Fremont, CA (Participants who are from outside the Bay Area may work virtually)
Cost: $1,070 (full financial aid available)
Acceptance Rate/Cohort Size: 75% (Early); 25% (Regular) | The number of open research positions changes each year
Program Dates: January 16 – May 30
Application Deadline: August 15 – December 30; priority deadline is November 15
Eligibility: High school students
This program offers high school students the chance to pursue original research in STEM fields, including AI-focused areas such as machine learning, deep learning, quantum computing, and autonomous vehicle research. Unlike traditional classroom settings, ASDRP places you in a professional lab environment where you’ll work closely with research mentors to design and execute projects that expand current scientific knowledge. You’ll develop skills in data analysis, technical writing, experimental design, and public speaking while engaging with topics like algorithmic bias and the societal impacts of AI. Throughout the program, you’ll have opportunities to publish your work in the ASDRP Communications online journal, undergo mock peer review, and present your findings in poster sessions. ASDRP runs three cohorts a year, including the Spring Term, which begins in January and coincides with the winter months.
8. MIT THINK Scholars Program
Location: Virtual | Finalists might get invited on a four-day, all-expenses-paid trip to MIT's campus
Cost/Stipend: Free | Selected finalists get up to $1,000 in funding for their projects
Acceptance Rate/Cohort Size: Up to 6 finalists will be chosen
Program Dates: Semifinalists will be announced on January 30 and finalists on February 5 | Finalists have until June to complete their projects
Application Deadline: November 1 – January 1
Eligibility: Open to all U.S. high school students
The MIT THINK Scholars Program is a national research initiative that supports high school students with innovative ideas in science, technology, and engineering, including projects in artificial intelligence and machine learning. The program is designed to support students who have well-developed research ideas but lack the resources to carry them out. If selected as a finalist, you’ll receive up to $1,000 in funding, weekly mentorship from MIT students, and an all-expenses-paid trip to MIT, where you can tour labs, meet professors, and present your project. Past AI-related finalist projects have included work on contrail reduction using computer vision and the use of autonomous robots for species monitoring. Throughout the program, you’ll strengthen skills in research design, project management, and problem-solving while gaining exposure to how innovation is pursued at MIT.
9. Stanford’s Center for Artificial Intelligence in Medicine & Imaging (AIMI) Academic Year Research Internship
Location: Virtual
Cost: $4,800 (need-based scholarships available)
Acceptance Rate/Cohort Size: Limited number of seats available, with preference given to alumni of the AIMI Summer Research Internship and Summer Health AI Bootcamp program
Program Dates: September 29 – June 5
Application Deadline: Registration is first-come, first-served
Eligibility: High school students, but with first preference given to alumni of the AIMI Summer Research Internship and Summer Health AI Bootcamp programs
In the Stanford AIMI Academic Year Research Internship, you’ll join a small group of peers to work on original projects in AI for health and medicine, guided by Stanford student mentors. Each week, you’ll participate in a one-hour mentorship session, spend 2–4 hours on independent and group work, and have the option to attend office hours for extra support. Projects range from technical work—such as data analysis, building and testing AI models, and scientific writing—to non-technical explorations of ethics, policy, and bias in healthcare AI. You’ll also have the chance to join enrichment activities, including quarterly “Meet the Experts” sessions with leaders in the field, to broaden your perspective on AI in healthcare and explore new career pathways. At the end of the program, you’ll present your findings in a Student Showcase during Stanford Health AI Week, with some groups also preparing abstracts for conferences or journals in collaboration with their mentors.
10. NC State’s Global Training Initiative: Online Research Academy
Location: Virtual
Cost: $1,295/student (early bird discount and partial scholarships available)
Acceptance Rate/Cohort Size: Not specified
Program Dates: January 28 – March 12 (winter session)
Application Deadline: October 1 – January 4 (early bird discount for the winter session ends on November 16)
Eligibility: High school sophomores, juniors, and seniors | Prerequisites might vary depending on the research project you choose. Check the project syllabus here for more information
In this program, you’ll take part in a four-week virtual research experience led by faculty from North Carolina State University and the University of North Carolina Wilmington.
You can choose from AI-related research topics, such as AI for Loan Applications or Digital Marketing Campaigns: AI & Communication Research. Depending on the track, you may learn to use Python-based tools to build predictive models for loan approval or AI to design and analyze marketing strategies. Coursework might include data gathering, exploratory data analysis, model development, content analysis, and project presentations, with regular mentorship meetings twice a week. You’ll work both independently and in collaboration with peers on AI-based research projects, gaining practice in research design, quantitative methods, and scientific communication. By the end of the program, you’ll complete a final project, present your results, and receive a graduation certificate and performance evaluation letter from your professor.
11. Google’s Machine Learning Crash Course
Location: Virtual
Cost: Free
Acceptance Rate/Cohort Size: Fairly welcoming and open to everyone
Program Dates: Available year-round; self-paced
Application Deadline: Not applicable
Eligibility: Open to everyone, including high school students | Recommended prerequisites: Algebra, Linear Algebra, Trigonometry, Statistics, and optionally Calculus
In Google’s Machine Learning Crash Course, you’ll work through a series of structured modules that cover the fundamentals of regression, classification, data handling, and neural networks, each reinforced with short video lessons, interactive visualizations, and coding exercises. You’ll learn how to prepare and analyze data, build and evaluate models, and explore more advanced topics like embeddings, large language models, and fairness in AI. The course also gives you an inside look at how production ML systems operate, along with best practices for automation and real-world deployment. Each module is self-contained, so you can follow the full sequence or focus on specific areas based on your background and goals. By the end, you’ll have gained hands-on practice with key machine learning techniques and a stronger understanding of how these methods are applied in real-world AI systems.
12. Northwestern’s Online Honors Courses – Machine Learning: Algorithms & Data Science
Location: Virtual
Cost: $835 (1 credit) | Financial aid available
Acceptance Rate/Cohort Size: Not specified
Program Dates: January 21 – May 20 (Winter)
Application Deadline: Rolling enrollment | Last date for late application submissions for Winter cohort is January 28
Eligibility: High school students | Click here for more information (this is a Magenta Tier course)
In Northwestern’s Online Honors Course Machine Learning: Algorithms & Data Science, you’ll study how AI uses data to recognize patterns, make predictions, and perform tasks that appear “intelligent.” The curriculum covers core topics such as regression, classification, clustering, dimensionality reduction, deep learning, and neural networks. You’ll also work with tools like Python or WEKA to practice coding, test algorithms, and apply methods to real datasets. A key feature of the course is the final project, where you’ll design and evaluate your own supervised machine learning algorithm. Along the way, you’ll receive individualized instructor feedback and join two virtual meetings with peers to share insights and showcase your work. You will be expected to spend 6–8 hours per week on coursework during the school year, giving you a structured yet flexible way to build applied AI skills.
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