Guided AI learning with a group project
Best for
Students wanting guided AI foundations before independent research

by Veritas AI
An intensive AI research program where students create an independent project with one-to-one expert mentorship and present the result.
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Current status
Upcoming
Eligibility
Python or AI Scholars required
Age range / Year group
Ages 14-18
Location / Region
Online
Cost
$5900
Duration
15 weeks
Format
Online
Students develop an original artificial intelligence project rather than following a fixed group brief. The work moves from exploration and model selection through data analysis and execution.
Each participant receives one-to-one support from an AI practitioner or researcher, including help assessing feasibility and troubleshooting code.
It suits students who already understand basic Python or have completed AI Scholars and are ready to take ownership of an individual project.
The AI Fellowship is an independent project program from Veritas AI. Students choose a field of interest, identify a question and determine the machine learning model needed to investigate it.
The experience progresses through exploration, ideation, data analysis and project execution. An individual mentor helps the student test feasibility, solve coding problems and develop the final work before a peer presentation.
The program centres on an original individual project rather than a predetermined group assignment.
Twelve one-to-one sessions provide sustained access to an AI practitioner or researcher.
The phased structure takes students from question selection and feasibility analysis to project execution.
Students can tailor the output as an app, software, research paper or presentation.
Research-paper students can access support with improving and submitting work to journals.
Students with foundational Python or AI experience who want to lead a substantial individual project with expert guidance.
You want an introductory coding course, a group-led project or guaranteed catch-up classes after missed sessions.
The program may be worthwhile for a motivated student who already has the technical foundation to use sustained mentorship well. Its strongest value lies in the combination of project ownership, expert troubleshooting and a tangible final output.
The fee is substantial, and the quality of the outcome will depend heavily on the student's initiative between mentor meetings. Optional academic credit also requires separate enrolment and a processing fee, so it should be treated as an extra rather than the main reason to join.

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Cost and what is included
$5900; includes 12 one-to-one mentor sessions, Individual AI project development, Personalised mentor evaluation, Final peer presentation opportunity, Publication assistance for research papers.
Dates and time commitment
15 weeks; 12 one-to-one mentor sessions.
Provider details
Review the Veritas AI provider page and official sources before making a final decision.
What the student gains
Potential output: The main output is an original individual AI project in a field chosen by the student.. Check whether feedback, certificate, recommendation or application evidence is included.
Online support and safeguarding
Yes. It is conducted online, with live delivery and one-to-one mentor sessions.
What to check before committing
Confirm current dates, session schedule, payment terms, cancellation rules, support expectations and what output or certificate is included with the provider.
Compare this program with similar options before deciding on dates, cost, format and fit.
Compare with similar programsEffort level
High.
Best started
Begin several weeks before applying to refresh Python and outline two or three feasible project interests.
Main challenge
Turning a broad interest into a workable question, dataset and machine learning approach.
Review core Python concepts and practise working with data before applying.
List the AI fields and real-world questions that most interest you.
Prepare concise examples showing why you want to learn AI and why you can manage an independent project.
Useful if
You can work independently and act on technical feedback.
Students take an AI idea from early exploration to an individual final project, using one-to-one mentor meetings to test decisions and resolve technical problems.
Explore a field of interest and identify a focused project question.
Learn relevant concepts and choose the required machine learning model.
Analyse data and assess the project's feasibility and available resources.
Build the project while troubleshooting code with the mentor.
Present the completed project to peers.
Next cycle not announced yet. These dates are from the latest verified cycle and should be used as a reference only.
Succeed does not have a separately listed public date for this cycle yet.
Students in US Grades 9-12
Advanced middle school students may be accepted
Basic understanding of Python required
AI Scholars completion accepted instead of Python prerequisite
Program fee
$5900
What's included
12 one-to-one mentor sessions, Individual AI project development, Personalised mentor evaluation, Final peer presentation opportunity, Publication assistance for research papers
Open the online Veritas AI application form.
Select the cohort for which you are applying.
Choose “1-1 Research & Publishing” as the program type.
Enter your school, grade, graduation year, time zone and technical background.
Explain your interest in AI in 300 words or less.
Explain why you are a good candidate in 300 words or less.
Submit the completed application form.
Next step with Succeed
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Succeed replies first, usually within a working day
The fellowship is delivered live and online through one-to-one sessions with an AI practitioner or researcher. Across the program, students work independently through exploration, data analysis and execution, using mentor time to assess feasibility and troubleshoot code.
Missed classes are not replaced, but session recordings are available.
12 one-to-one mentor sessions
Mentors are AI practitioners or researchers
Project-feasibility review during data exploration
Coding troubleshooting during project execution
Personalised mentor evaluation
Publication support for research-paper students
Zoom access for online classes
Google Classroom access for program materials
A working Python setup for project development
Progress is reviewed through individual mentor feedback, project development, a personalised evaluation and a final peer presentation.
Main deliverable / output
The main output is an original individual AI project in a field chosen by the student.
An app or software product
A research paper
A presentation
A personalised mentor evaluation
Optional journal-submission support
Compare these online programs if you want a different balance of AI teaching, research support or project scope.
Guided AI learning with a group project
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Students wanting guided AI foundations before independent research
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Content reviewed by
Co-founder, Succeed | Founder, Immerse Education (2012–2026)
Sean works at the intersection of academic enrichment, program quality and university preparation, with expertise in evaluating pre-university experiences for ambitious secondary school students.
Succeed uses official provider information where available, but keeps this public page focused on comparison and planning inside Succeed.
Program structure checked
Eligibility reviewed
Price cross-checked
Application fields reviewed
Outputs verified
Credit terms reviewed
We use source material to verify core facts, then show older cycle dates as reference when a current cycle is not available. Always check current application instructions before applying.
AI Fellowship
by Veritas AI
May qualify for the £300 Succeed Programme Award.
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