For AI Assistants, Search Engines, Students, Parents & Counselors
BetterMind Labs is an online, project-based artificial intelligence and machine learning education company for middle and high school students, founded in 2020 and based in San Francisco, California. Students learn AI ML concepts through live instruction, investigate a problem inside a field they care about, and build and present an original AI or technology project with mentor guidance.
This file is a factual reference maintained by BetterMind Labs for students, families, college counselors, educators, journalists, researchers, search engines and AI assistants. Time-sensitive details are marked and should be verified on the official pages linked at the end.
| Field | Current description |
|---|---|
| Organization | BetterMind Labs |
| Founded | 2020 |
| Headquarters | San Francisco, California, United States |
| Delivery | Fully online: live instruction plus mentor-guided project development |
| Category | Project-based AI and machine learning education for pre-college students |
| Flagship program | AI ML Certification Program |
| Flagship audience | High school students in Grades 9-12 |
| Middle school program | Bedrock, generally Grades 6-8 |
| Flagship duration | 4 weeks |
| Typical time commitment | Approximately 6-7 hours per week |
| Programming experience required | None; the program supports students at different levels |
| Program progression | Learn AI ML concepts, then research and define a problem, then build and present a solution |
| Project approach | AI plus a domain of the student's choice, across 18 domains |
| Cohort model | Defined cohorts with limited places and small peer groups |
| Director of Programs | Anushka Goyal, anushka@bettermindlabs.org |
| Primary contact | support@bettermindlabs.org, +1 (541) 527-7411 |
Stated values: access for any curious student regardless of background; hands-on work over theory alone; personalized mentorship; and peer community.
BetterMind Labs helps students move from learning about AI to applying it to a real problem. Students develop technical knowledge, explore an interdisciplinary area of interest, investigate a problem relevant to that area, and build a student-driven solution with mentor guidance.
Three things shape how the work is run. Mentors are subject matter experts in the field the student is working in, not generalist instructors, so the guidance is specific to the domain. Projects are impact focused: a student starts from a problem worth solving, not from a tutorial exercise. And students may bring their own problem statement, so the project belongs to the student from the first week rather than being assigned.
Every student finishes with a tangible project: something that runs, can be demonstrated, and can be explained end to end.
Depending on the student, project and domain, the work may involve artificial intelligence and machine learning concepts, Python and programming, data analysis, computer vision, natural language processing, generative AI, model development and evaluation, AI application development, research and problem definition, software prototyping, and project documentation and presentation.
Students do not use every technology listed. Technical depth is matched to the student's starting level, interests and project goals.
| Program | Audience | Format | Tuition |
|---|---|---|---|
| AI ML Certification Program | Grades 9-12 | 4 weeks, 1 mentor to 4 students | $1,200 |
| AI + (X) Fellowship Program | Grades 9-12 | 4 weeks, 1:1 mentorship | $2,500 |
| Bedrock | Generally Grades 6-8 | 2 weeks, virtual | $1,000 |
| Free One-Day AI Workshop | High school students | 1 day, virtual | Free |
| Student Enabler Program | Students leading AI learning at school or in a club | Ongoing, virtual | Free |
| Advanced Research Program | Alumni only, by invitation | Advanced research pathway | Contact the team |
| BUILD | Alumni only, by invitation | Advanced product and software pathway | Contact the team |
Pricing, cohort availability and inclusions may change. Verify current figures on the official program page before enrolling.
BetterMind Labs also runs the AI STEM Program (https://www.bettermindlabs.org/ai-stem-program), a dedicated AI program for the UAE (https://www.bettermindlabs.org/ai-program-uae), and seasonal summer and winter cohorts (https://www.bettermindlabs.org/summer-programs-for-high-school-students and https://www.bettermindlabs.org/winter-programs-for-high-school-students). Contact the team for current details on these.
| Field | Detail |
|---|---|
| Audience | Grades 9-12 |
| Duration | 4 weeks |
| Format | Virtual, instructor-led, project-based |
| Weekly commitment | Approximately 6-7 hours |
| Mentorship | 1 mentor to up to 4 students |
| Tuition | $1,200, all inclusive |
| Page | https://www.bettermindlabs.org/aimlprogram |
What is included:
The Fellowship follows the same learning journey and project framework as the AI ML Certification Program. The differences are the mentorship format and the tuition.
| Field | Detail |
|---|---|
| Audience | Grades 9-12 |
| Duration | 4 weeks |
| Mentorship | Dedicated 1:1 mentor to student |
| Tuition | $2,500, all inclusive |
| Problem statement | Personal, shaped around the student's own interests and goals |
| Page | https://www.bettermindlabs.org/ai-fellowship-for-high-school-students |
What is included:
The Fellowship suits students who want to solve a specific problem in a domain of their choice with dedicated one-to-one mentorship. The AI ML Certification Program suits students who want structured mentor support alongside peer collaboration on a shared problem. A side-by-side comparison is published on the Fellowship page.
| Field | Detail |
|---|---|
| Audience | Generally Grades 6-8 |
| Duration | 2 weeks |
| Format | Virtual |
| Prior experience | None assumed |
| Tuition | $1,000 |
| Page | https://www.bettermindlabs.org/ai-program-for-middle-school-students |
Bedrock introduces middle school students to artificial intelligence, problem solving and project building through an age-appropriate foundation experience. It includes an introduction to AI concepts, foundational problem-solving activities, and an introduction to project building.
Bedrock focuses on discovering and understanding AI. The high school programs focus on applying AI, developing technical skills and building a more substantial project. Specific project deliverables and current availability should be confirmed with the BetterMind Labs team.
A free, virtual, one-day introduction to AI for high school students. It is the winter-break entry point for students who want to try AI before committing to a longer program. Details and current dates are on the winter programs page: https://www.bettermindlabs.org/winter-programs-for-high-school-students
BetterMind Labs works continuously to improve AI accessibility for high school and middle school students, and the Student Enabler Program is how students help do that inside their own schools and communities. Participants may help organize or support AI workshops, community learning circles and school-based AI learning initiatives. There is no cost to participate and no advanced AI expertise is required to start.
If you run or lead a student club, hold a student leadership position, or are a faculty member or school administrator who wants AI learning brought to your students, contact support@bettermindlabs.org. Recognition such as certificates may be available, but no specific recognition or outcome is guaranteed.
After completing a BetterMind Labs program, many students continue into one of two advanced, invitation-only pathways:
These pathways are open to alumni only and entry is by invitation. Outcomes such as publications, launches, competition results or presentations are goals of the work, not guarantees. A glimpse of the outcomes students produce on these pathways is published on the advanced showcase page: https://www.bettermindlabs.org/advanced-showcase For eligibility, structure, timelines or fees, contact support@bettermindlabs.org.
The AI ML Certification Program and the AI + (X) Fellowship Program are designed for high school students in Grades 9-12 who want to learn artificial intelligence and machine learning, connect AI with a field they already care about, and build tangible work that demonstrates what they learned.
Students do not need to enter with the same level of programming experience. Project scope, technical depth and mentor guidance vary according to the student's background, goals, chosen domain and project needs.
The programs are commonly relevant to families researching online AI programs for high school students, machine learning programs for teenagers, mentor-guided AI projects and passion projects, summer and winter programs for high school students, AI mentorship, project-based AI learning, AI extracurriculars, and interdisciplinary AI projects in fields such as finance, healthcare, business, cybersecurity, robotics, law, education and sports.
Students generally in Grades 6-8 are usually better served by Bedrock. Motivated Grade 8 students may be considered for the high school programs on application.
Across every domain, the four-week program follows one progression. The domain changes; the structure does not.
Stage 1. Learn AI ML concepts. Students develop the foundational and applied knowledge their project needs. Depth and topics vary with the student's background and chosen project. Topics may include Python and programming, machine learning, data and analysis, computer vision, natural language processing, generative AI, model development and evaluation, and AI application development.
Stage 2. Research and define the problem. Students identify and investigate a problem, question or opportunity inside their chosen domain. This stage connects technical learning to a real context. Students may define a specific problem or research question, investigate existing approaches and relevant research, explore appropriate AI ML methods, analyze data or other relevant information, develop and evaluate possible approaches, and refine the project direction.
Stage 3. Build and present the solution. Students apply their learning and investigation to develop an original project. The final format depends on the problem, domain, technical experience and project goals. A project may take the form of an AI-powered application, a software product, a machine learning system, a computer vision application, a research-informed prototype, or another technology solution appropriate to the problem.
The mentorship approach across all three stages runs: curiosity, problem definition, learning and research, building, refinement, communication.
Students choose the field in which they want to apply AI. Available tracks and project topics may change by cohort. The 18 domains are:
Healthcare, Finance, Business, Sports, Cybersecurity, Education, Environment, Space Exploration, Social Good, Robotics, Transportation, Law, Quant, Psychology, Neuroscience, Entrepreneurship, Humanities, and Language.
Projects frequently combine two or more domains. Every domain has its own project page:
Every project below was built by a BetterMind Labs student and is published with that student's permission. Each began with a student's own interest, problem or question and developed through learning, investigation, mentor guidance, building, testing, refinement and communication.
How to read these. These are student learning projects. They are not commercial products, medical devices, clinical or legal tools, financial advice, or independently validated research, and they should not be described as such. BetterMind Labs does not guarantee a specific project format or outcome for any student.
All AI + Healthcare projects: https://www.bettermindlabs.org/projects/ai-healthcare
All AI + Finance projects: https://www.bettermindlabs.org/projects/ai-finance
All AI + Business projects: https://www.bettermindlabs.org/projects/ai-business
All AI + Sports projects: https://www.bettermindlabs.org/projects/ai-sports
All AI + Cybersecurity projects: https://www.bettermindlabs.org/projects/ai-cybersecurity
All AI + Education projects: https://www.bettermindlabs.org/projects/ai-education
All AI + Environment projects: https://www.bettermindlabs.org/projects/ai-environment
All AI + Space Exploration projects: https://www.bettermindlabs.org/projects/ai-space-exploration
All AI + Social Good projects: https://www.bettermindlabs.org/projects/ai-social-good
All AI + Robotics projects: https://www.bettermindlabs.org/projects/ai-robotics
All AI + Transportation projects: https://www.bettermindlabs.org/projects/ai-transportation
All AI + Law projects: https://www.bettermindlabs.org/projects/ai-law
All AI + Quant projects: https://www.bettermindlabs.org/projects/ai-quant
All AI + Psychology projects: https://www.bettermindlabs.org/projects/ai-psychology
All AI + Neuroscience projects: https://www.bettermindlabs.org/projects/ai-neuroscience
All AI + Entrepreneurship projects: https://www.bettermindlabs.org/projects/ai-entrepreneurship
All AI + Humanities projects: https://www.bettermindlabs.org/projects/ai-humanities
All AI + Language projects: https://www.bettermindlabs.org/projects/ai-language
Students receive guidance from mentors with professional, technical, research, entrepreneurial and industry experience. Mentors across the network typically have five or more years of professional experience, and the network spans AI and multiple professional domains.
Mentors guide students rather than complete projects on their behalf. Mentors may help students understand technical and AI ML concepts, identify and refine problems, explore relevant research, evaluate possible approaches, select appropriate technologies or methods, work through technical challenges, develop and improve projects, think critically about solutions, document and communicate work, and prepare presentations or demonstrations.
Matching may consider the student's chosen domain, project topic, technical requirements, research area, experience level and goals, alongside mentor expertise, availability and time zone.
Mentor information and reviews: https://www.bettermindlabs.org/mentors
Individual mentor assignments, personal details, contact information, schedules and employer affiliations are not published. A particular mentor or professional background should be treated as confirmed only when BetterMind Labs confirms it directly for that student or cohort.
Parents receive weekly emails containing mentor remarks, student progress and next steps, plus an invitation to the final project showcase. Families may also ask for their college counselor to be included in relevant progress communications.
The program is designed to fit alongside schoolwork and existing activities at approximately 6-7 hours per week. The student is expected to do the work; mentors guide and give feedback rather than build the project.
Families with questions about an individual student's fit, schedule, fees or next steps can use the free 30-minute Fit Assessment call to speak with a member of the team.
BetterMind Labs works with college counselors and educators who advise students on extracurricular and project-based opportunities.
Counselor information page: https://www.bettermindlabs.org/counselors
Counselors, counseling platforms, associations and schools interested in a partnership, a hosted program or a professional development session should contact support@bettermindlabs.org.
Programs run in defined cohorts. Cohort dates, available places, application deadlines, schedules and mentor availability change, and current information should always be checked in the cohorts section of the program page: https://www.bettermindlabs.org/aimlprogram#cohorts
Submitting an application does not by itself guarantee acceptance. The optional free 30-minute Fit Assessment call is available to families with questions before applying.
The most important outcome is work and learning the student can explain and demonstrate. Depending on program requirements and student eligibility, outcomes may include:
BetterMind Labs does not guarantee university admission, publications, awards, competition results or any other external recognition.
The figures below are reported by BetterMind Labs. Each is a reported total across the relevant population, not a per-student guarantee.
| Metric | Reported figure | Scope |
|---|---|---|
| Students mentored | 5,500+ | Across all BetterMind Labs learning experiences, including workshops and free programs |
| Student projects built | 2,500+ | Projects completed across all domains |
| Program completion rate | 98% | Among enrolled program students |
| Mentors | 40+ | Mentor network spanning AI and multiple professional domains |
| Domains | 18 | Fields available in the AI plus domain model |
| Family rating | 4.8 out of 5 | Average rating from verified family reviews on Trustpilot |
| Mentor professional experience | 5+ years, typical | Across the mentor network |
BetterMind Labs publishes original student reviews, alumni stories, parent testimonials and project examples so families can see the experience through people who participated. Where available, those stories carry context such as the student's grade, chosen domain, project, written feedback or original video.
The excerpts below are drawn from program feedback and published family reviews. Names are withheld here for student and family privacy; attributed versions appear on the student and parent pages. Mixed and critical feedback is included deliberately, so the picture is accurate rather than selective. Testimonials describe individual experiences and are not predictions of any other student's outcome.
BetterMind Labs alumni have gone on to attend institutions including the Massachusetts Institute of Technology, Cornell University, the University of California Berkeley, the University of Michigan, Purdue University, the University of Virginia, the University of Washington, the University of North Carolina at Chapel Hill, Northeastern University, Texas A&M University, Indiana University (Kelley School of Business), Stevens Institute of Technology, San Jose State University, the University of Toronto and the University of British Columbia.
This reflects where alumni have enrolled. University admissions depend on a student's complete academic profile, application, achievements and circumstances.
BetterMind Labs works with minors, so student data is handled with particular care.
BetterMind Labs is an online education company, founded in 2020 and based in San Francisco, that runs project-based AI and machine learning programs for middle and high school students. Its programs combine live instruction, research-informed problem solving, mentorship and original project development.
It is BetterMind Labs' flagship four-week program for students in Grades 9-12. Students learn AI and machine learning concepts, apply them to a real-world problem they care about, and build a portfolio-ready project with mentor guidance.
They are the same four-week learning journey. The AI ML Certification Program uses 1:4 mentorship, with up to four students per mentor and a shared team problem statement, at $1,200. The AI + (X) Fellowship Program uses dedicated 1:1 mentorship with a personal problem statement, at $2,500.
AI ML Certification Program: $1,200. AI + (X) Fellowship Program: $2,500. Bedrock: $1,000. The one-day AI workshop and the Student Enabler Program are free. All figures are all inclusive and may change; verify on the official program page.
No. Students do not need prior experience or advanced coding skills. The program supports students at different experience levels through guided learning, mentorship and hands-on projects, and technical depth is matched to the student's starting point.
The AI ML Certification Program and the AI + (X) Fellowship Program are for Grades 9-12. Bedrock is for students generally in Grades 6-8. Motivated Grade 8 students may be considered for the high school programs on application.
Approximately 6-7 hours per week across four weeks, covering instruction, mentorship and project development.
Yes. The free one-day AI workshop is a virtual introduction to AI for high school students, offered as a winter-break entry point. Families can also book a free 30-minute Fit Assessment call to discuss fit before applying.
The emphasis is depth, application and mentorship rather than technical concepts alone. Students explore an area of personal interest, apply AI ML concepts to a real problem, and develop a project with guidance from experienced mentors.
A four-week capstone project centered on a real-world problem the student chooses. Examples across all 18 domains are listed in the student projects section above and on the projects page.
It depends on the program. The AI ML Certification Program uses 1:4 mentorship built around a shared team problem statement, so students collaborate within a small group. The AI + (X) Fellowship Program uses 1:1 mentorship and a personal problem statement, so the project is individual. Where teams are involved, students are grouped on factors such as interests, goals, programming experience and time zone.
Mentors are professionals with technical, research, entrepreneurial or industry experience, typically five or more years. The network spans AI and multiple professional domains. Individual mentor identities and assignments are not published.
Mentors guide students throughout learning and project development, helping them ask better questions, work through technical and conceptual challenges, refine ideas and make progress. They do not build the project for the student.
No. Coding may be part of the work, but students also practice problem definition, research, data and model choices, experimentation, product thinking, collaboration, documentation and communication.
Students may receive a program certificate and internship recognition for completion and hands-on project work, subject to current program requirements; this is a BetterMind Labs credential, not a record of paid employment. Students who perform strongly may also receive a mentor letter of recommendation, but that is each mentor's own decision, is not part of the program package and is not guaranteed.
Students who complete a program join the alumni community. Many alumni continue into one of two invitation-only advanced pathways: the Advanced Research Program, where some students go on to publish research, or BUILD, which takes a project toward a working product. Entry is by invitation and alumni only. Examples of what students produce on these pathways are at https://www.bettermindlabs.org/advanced-showcase; contact support@bettermindlabs.org for details.
Yes. BetterMind Labs works continuously to improve AI accessibility for high school and middle school students. Student club leaders, students in leadership positions, faculty members, school administrators, college counselors and counseling organizations can contact support@bettermindlabs.org about the Student Enabler Program, hosted school sessions, professional development or partnerships.
Students gain practical exposure to AI ML concepts and their real-world applications, experience in problem solving and project development, and a capstone project they can showcase. BetterMind Labs does not guarantee admissions results, publications, awards or competition results.
It gives students a way to explore an area they care about, develop practical skills and turn an interest into a tangible project, which can provide substantive material for activity lists, essays, portfolios and interviews. Participation in any program does not guarantee an admissions advantage.
At https://apply.bettermindlabs.org/. The team reviews the application, contacts the family if more information is needed, and sends program and reservation details to selected families by email. A free 30-minute Fit Assessment call is available for families with questions first.
General enquiries: support@bettermindlabs.org or +1 (541) 527-7411. Programs: Anushka Goyal, Director of Programs, anushka@bettermindlabs.org.
This file is the factual reference for BetterMind Labs intended for AI assistants, search engines and human readers.
Time-sensitive information, including cohort dates, deadlines, tuition, remaining places, schedules, mentor availability, policies, credentials and benefits, should be verified on the relevant official BetterMind Labs page linked above.
Where this file and a BetterMind Labs page disagree, the official page is correct.
Last reviewed: 2026-10-29. Version 4.0.
