If you’re a high school student interested in technology and want to understand how artificial intelligence really works, a fall machine learning program can be a good place to begin. These programs teach you how to build and train models, analyze data, and apply coding skills to real-world problems. You’ll learn how machines recognize patterns, make predictions, and improve over time.
Many of these programs also include topics connected to AI, like computer science, data science, web development, and the ethics of technology. You’ll work on small projects that involve datasets, guided by mentors from universities or research labs. Through this, you’ll learn how to think like a programmer and approach problems methodically.
Joining one of these programs during the fall helps you use your school year productively while building experience that can help later in college. You’ll improve your technical skills, practice teamwork, and start to understand how AI and machine learning are shaping industries like healthcare, business, and education.
With that, here’s a list of 13 fall machine learning programs for high school students to explore this season!
13 Fall Machine Learning Programs for High School Students
1. The Air Force Research Laboratory (AFRL) Scholars Program
Location: Several AFRL across the U.S. Click here to learn more
Cost | Stipend: Free | Stipend varies based on education level and project site—check here!
Program Dates: Program dates vary based on location and project
Application Deadline: Varies based on location and project
Eligibility: U.S. students who are at least 16 years old (must be at least 18 to work at the California locations) | Minimum GPA of 3.0/4.0 is preferred, but not necessary | More information available here.
In the AFRL Scholars Program, you’ll work alongside scientists and engineers on research projects that often involve artificial intelligence and machine learning. Previous internships for high school students have involved projects such as developing hierarchical reinforcement learning algorithms for cooperative swarms and applying data science techniques to analyze hyperspectral and hypertemporal signals from space systems. Through these projects, you’ll build technical skills in programming, algorithm design, and data analysis while contributing to defense and aerospace research. You will also receive full-time guidance from highly knowledgeable AFRL mentors at every step of your internship.
2. The New York Academy of Sciences – The Junior Academy
Location: Virtual
Cost: Free
Program Dates: The challenge takes place twice a year, in the Fall and Spring. The Fall Semester takes place for three months in September – November.
Application Deadline: March 27 – July 8 (Fall Semester)
Eligibility: Students aged 13–17 who possess a strong level of English proficiency
The New York Academy of Sciences’ Junior Academy is a virtual, semester-long program that connects high school students from around the world as they collaborate on research-based projects addressing real-world challenges in areas like health, sustainability, and technology. Working in international teams, you’ll use the Academy’s Launchpad platform to design innovative solutions with guidance from STEM experts in academia and industry. You will also present your team’s solutions to a panel of STEM professionals. Past student teams have integrated machine learning and artificial intelligence into their solutions, applying convolutional neural networks to detect plant diseases, using predictive models to monitor wildfire spread, and creating machine learning models to detect oil spills. These challenges allow you to go beyond theory, experimenting with data science tools and algorithms to solve pressing global problems.
3. Los Alamos National Laboratory High School Internships
Location: Los Alamos National Laboratory, Los Alamos, NM
Cost | Stipend: None | $16.89/hour
Program Dates: Internships are available throughout the year, including the Fall.
Application Deadline: August 1 – September 30 (Fall Internships)
Eligibility: Open to high-school seniors aged 16+, U.S. citizens or authorized to work, with housing/transport arranged if non-NM residents. Minimum 2.75 GPA; pass standard background and drug screening.
The Los Alamos National Laboratory (LANL) High School Internship Program offers part-time research opportunities for students during the school year. As a Fall intern, you will work 10–20 hours a week alongside LANL scientists on active research projects. Possible projects can cover areas like bioinformatics, computational protein engineering, and artificial intelligence applications in chemistry and nanotechnology. For example, you might use machine learning to study protein structures, apply AI tools to extract and organize chemistry data, or develop code to analyze electron microscopy images of quantum dots. This hands-on experience will let you develop skills in problem-solving, coding, and data analysis, while contributing to research that serves national interests.
4. Columbia University’s Academic Year Weekend Programs – Data Science and Machine Learning I
Location: Virtual
Cost: $2,810 + $80 application fee
Program Dates: September 19 – December 7 (Fall session)
Application Deadline: Not specified
Eligibility: High school students with little to no experience with coding or programming
Columbia University’s Academic Year Weekend Program on Data Science and Machine Learning I is a fall course designed for high school students in grades 9–12. The program introduces you to the core concepts of data science and machine learning while building your skills in Python programming. Over the course of ten weekends, you’ll explore real-world applications of algorithms and learn how data science methods and machine learning models intersect. By the end of the program, you’ll be able to analyze datasets, apply introductory ML techniques, and present data ethically and effectively.
5. Stanford AIMI’s Academic Year Research Internship
Location: Virtual
Cost: $4,800 (need-based scholarships available)
Program Dates: September 29 – June 5
Application Deadline: Registration is first-come, first-served
Eligibility: High school students, but with preference given to alumni of the AIMI Summer Research Internship and Summer Health AI Bootcamp programs
Stanford AIMI’s Academic Year Research Internship is a 30-week virtual program where you will work independently and in small groups on original health AI projects guided by Stanford student mentors. Depending on your interests, you might build and test machine learning models with medical datasets, conduct exploratory data analysis, or write literature reviews on topics like deep learning applications in imaging or bias in clinical AI systems. You will also practice skills in scientific writing, oral presentations, and data-driven problem solving, with opportunities to submit abstracts to journals or conferences. The program emphasizes both technical and non-technical aspects of AI in healthcare, covering areas such as algorithm design, ethics, and implementation challenges.
6. NASA International Space Apps Challenge
Location: Multiple locations across the globe. Click here to find a local event near you!
Cost: Free
Cohort Size: Participating teams must have no more than 6 members
Program Dates: October 4–5
Application Deadline: Registration is open until the hackathon ends on October 5
Eligibility: Open to everyone, including high school students
The NASA International Space Apps Challenge is a two-day global hackathon that invites students, coders, engineers, scientists, and innovators to solve real-world problems using NASA’s open data. As a participant, you’ll work in teams to develop projects that address challenges in areas like space exploration, Earth science, and biology. Many of these challenges incorporate machine learning and AI, such as building models to detect exoplanets from Kepler and TESS datasets, creating AI-powered dashboards to organize decades of space biology experiments, or integrating cloud-based ML systems to forecast air quality using TEMPO satellite data. You’ll learn to work with large-scale datasets, explore a range of AI and machine learning techniques, and apply data science to space and Earth problems.
7. TECH360: Intro to AI
Location: The Fall session is mostly virtual, with required in-person sessions held on September 22, December 1, and December 3 in West Midtown Atlanta
Cost | Stipend: Free | $500
Program Dates: September 22 – December 3, with Demo Day on December 4 (Fall Program dates)
Application Deadline: Fall application deadline for the Atlanta location is in August
Eligibility: High school sophomores, juniors, or seniors between the ages of 15–19 | Must attend a public high school that meets America on Tech’s Economic Needs Index in Metro Atlanta
Hosted by America On Tech (AOT), TECH360: Intro to AI is a fall program that introduces Atlanta high school students to the principles and applications of artificial intelligence. Over the course of the program, you will explore how generative and predictive AI models are developed, learn concepts from data science and machine learning, and examine ethical considerations for AI use. The program culminates in a final group project where you’ll design and pitch an AI-powered tool to mock clients, with top projects being presented at Demo Day to a panel of judges. You will receive guidance from AOT mentors, gain insight into AI workflows, data analysis techniques, and model evaluation metrics, and interact with a network of peers interested in AI technology.
8. Johns Hopkins Applied Physics Laboratory’s (APL) ASPIRE Program
Location: In-person at Johns Hopkins APL, Laurel, MD; virtual placements available for students in Calvert or Charles Counties
Cost/Stipend: Unpaid; no cost to participate
Acceptance Rate: Highly selective (10%)
Program Dates: Summer: June 24 – August 21; Optional Academic Year Extension: September – May
Application Deadline: January 1 – February 15
Eligibility: High school juniors or seniors who are U.S. citizens, at least 15 years old, and reside in eligible counties in Maryland, Virginia, or the District of Columbia. Minimum GPA: 2.8
The ASPIRE program at Johns Hopkins Applied Physics Laboratory offers high school juniors and seniors a chance to dive into advanced STEM fields like AI, machine learning, computer science, and engineering. You will work closely with APL mentors on cutting-edge projects, such as detecting drone activity with deep learning, analyzing cyberspace anomalies, or evaluating AI-generated disinformation, while choosing from project tracks like coding, R&D, or electronics. Internships are available in-person or virtually, with the option to extend beyond summer into the academic year for a deeper research experience. If you plan to continue through the fall, be sure to balance your schedule, as the extended commitment ranges from 80 to 130 hours.
9. Tech Flex Leaders (TFL) Program
Location: Mostly virtual, with in-person sessions taking place at least 3 times a semester at Manhattan, Downtown Los Angeles, or Downtown Miami
Cost | Stipend: Free | Participants will receive a stipend, but the exact amount is not specified
Program Dates: Semester 1 (Fall Semester): Week of September 8 – December 16 | Semester 2 (Spring Semester): Week of January 19 – May 14
Application Deadline: May – August 3 (subject to change)
Eligibility: Rising high school juniors and seniors attending a New York City (all boroughs), Los Angeles County, or Miami-Dade/Broward County public or charter school
The TFL Program is a two-semester tech and AI immersion experience for high school students in NYC, LA, and Miami. In the first semester, you’ll build a foundation in web development (HTML, CSS, Bootstrap) and explore how generative and predictive AI tools work. In the second semester, you’ll choose a specialized track like Advanced Web Development, UX Design, Digital Marketing, Product Management, or Data Science. Each track integrates AI tools and techniques, with hands-on projects in coding, data mining, and machine learning. You’ll present your work at Demo Day, and NYC students who complete both semesters may qualify for paid internships and job opportunities through AOT’s employer network.
10. 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)
Program Dates: September 1 – January 15 (Fall term)
Application Deadline: May 1 – August 15 (Fall term)
Eligibility: Students currently enrolled in or entering grades 9–12
The ASDRP allows high school students to conduct original research in a range of STEM fields, including computer science, machine learning, artificial intelligence, and data science. You will work with research mentors from academia and industry to design projects in areas such as deep learning, data mining, AI algorithm bias, and computational physics. You will collect and analyze data, run simulations, develop coding workflows, and write a research paper that undergoes mock peer reviews. The program culminates in a final presentation where you share your findings with mentors and peers, and you also have the opportunity to publish your work in ASDRP Communications and other research journals.
11. Google’s Machine Learning Crash Course
Location: Online
Cost: Free
Program Dates: Self-paced
Application Deadline: Not applicable
Eligibility: Open to everyone, including high school students | Recommended prerequisites: Algebra, Linear Algebra, Trigonometry, Statistics, and optionally Calculus
Google offers this self-paced crash course in machine learning for high school students and beginners interested in AI. This is an online program that combines theoretical modules with interactive practice. Through lessons developed by Google researchers, you will study machine learning concepts like regression, classification, neural networks, embeddings, and large language models. There are also modules on datasets, production ML systems, and fairness in AI that teach you how to evaluate and deploy models responsibly. You’ll apply your learning through more than 100 coding exercises and visualizations, and at the end of the course, you will earn a certificate of completion.
12. Northwestern’s Online Honors Courses – Machine Learning: Algorithms & Data Science
Location: Online
Cost: $835 (1 credit) | Financial aid available
Program Dates: September 10 – January 14
Application Deadline: Rolling enrollment | Last date for late application submissions is October 1 (Fall session) | Tuition increases by $25 after September 12th for Fall sessions
Eligibility: High school students | Click here for more information (this is a Magenta Tier course)
Northwestern’s Online Honors Courses offer a flexible option for high school students looking to study machine learning in depth. The Machine Learning: Algorithms & Data Science course is available in a virtual format and covers topics such as regression, classification, clustering, neural networks, deep learning, and dimensionality reduction. You will learn how to preprocess datasets, select algorithms, build models, and evaluate their performance using programming tools like Python or WEKA. The course also emphasizes algorithm efficiency, model accuracy, and coding best practices through structured projects. Since this is a credit-bearing course, you can also earn high school credit while developing skills that prepare you for advanced study in computer science and data science.
13. MIT’s MITES Semester Program
Location: Virtual (with in-person MIT conference in summer)
Cost | Stipend: Free | No stipend
Program Dates: June through December (Fall phase: August – December with weekly webinars and college prep)
Application Deadline: February 1
Eligibility: U.S. citizens or permanent residents | High school juniors only | Students from underrepresented or underserved backgrounds strongly encouraged to apply
MITES Semester is a six-month hybrid program for high school seniors that blends advanced STEM coursework with college prep support. From June to August, you’ll take two rigorous online classes, choosing from project-based options like Machine Learning, Computational Biology, or Robotics, plus core subjects such as Calculus, Physics, Computer Science, or Science Writing. Past projects have included building neural networks and applying AI to real-world scientific challenges. From August to December, the focus shifts to college and career preparation. You’ll spend 3–5 hours per week in webinars, mock interviews, essay reviews, and mentorship sessions with MIT undergraduates.
One more option – Horizon Academic Research Program
If you’re looking for a competitive mentored research program in subjects like data science, machine learning, political theory, biology, and chemistry, 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 – The New York Academy of Sciences