For Ages 13–18 · Lagos, Nigeria
Your Child Builds AI.
Not Just Uses It.
A 12-week engineering-first accelerator where teenagers go from zero to building, training, and deploying real Machine Learning models; mentored directly by a Senior ML Engineer.
12wk
Intensive Programme Length
3
Tiers — Entry to Elite Fellowship
1
Capstone Project on GitHub
13–18
Target Age Range
Why This Programme is Different
Engineering vs. Entertainment
Most "tech camps" teach children to use software. This programme teaches them to engineer it.
Standard Holiday Tech Camps
Drag-and-drop block coding on Scratch, no real programming
Canva tutorials and graphic design labeled as "AI skills"
Generic certificates with no portfolio proof of capability
Instructors with no real-world engineering track record
Zero relevance to Ivy League or Russell Group admission portfolios
TOL AI Development Programme
Raw Python, NumPy, and Pandas; the actual tools used in industry
Train and deploy real foundational ML models with live data
Published GitHub portfolio project, proof employers and universities can verify
Direct 1-on-1 mentorship from a practicing Senior ML Engineer
Bespoke projects built for Ivy League / Russell Group admission portfolios
The 12-Week Curriculum
From Zero to ML Builder
A deliberately structured engineering pathway. Every phase builds on the last, ending in a real deployed model.
Phase 1
Programming Foundations
Weeks 1 – 4
- Python syntax, variables, and control flow
- Functions, classes, and data structures
- NumPy arrays and matrix operations
- Pandas for data loading and exploration
- Version control with Git & GitHub
Phase 2
Data & Model Engineering
Weeks 5 – 9
- Data cleaning, wrangling, and visualization
- Exploratory Data Analysis (EDA) techniques
- Supervised learning: regression and classification
- Model evaluation, metrics, and iteration
- Intro to neural networks and how they learn
Phase 3
Capstone & Global Demo Day
Weeks 10 – 12
- Independent capstone project (real African dataset)
- Model deployment to a live endpoint
- GitHub portfolio packaging and documentation
- Final presentation judged by tech executives
- Programme completion ceremony
Designed For
Parents Who Refuse Mediocrity
This programme is built for high-net-worth families who understand that standard schooling is not building the technical foundation their children need.
"My daughter's school teaches PowerPoint. She will be competing for internships against students who build ML pipelines. That gap terrified me."
— Parent Insight · Lagos, Nigeria
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C-Suite Executives & Managing Directors Banking, Oil & Gas, Telecoms, and premium consulting sectors
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Parents Targeting Ivy League Admissions Families with an explicit goal of placing their child into top US and UK universities, and who know a technical portfolio matters more than another extracurricular.
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Tech-Aware, Frustrated Parents You understand AI is reshaping the global economy. You've watched your teenager spend school holidays on social media while their global peers are building side projects.
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West African Diaspora & Expatriate Families Globally-minded parents based in Lagos, Accra, or Nairobi who want a technical foundation that holds up internationally.
Students Graduate With
Deployed ML Model
GitHub Portfolio
Python & NumPy Proficiency
Demo Day Presentation
University Admission Edge
Programme Investment
Choose Your Track
Three tiers designed to match your ambition for your child. Every track builds real engineering capability, the difference is the depth of mentorship and the goal.
Entry Track
The Future-Proof Bootcamp
₦53,750
/ month · 3 months
Total: ₦161,250 · Programme Duration: 3 Months
- Full 12-week live engineering lab access
- Step-by-step Python programming workbooks
- Weekly homework code reviews
- Capstone project and Demo Day entry
- Programme completion certificate
Most Popular
Core Track
The Young Architect
₦75,250
/ month · 3 months
Total: ₦225,750 · Programme Duration: 3 Months
- Everything in the Future-Proof Bootcamp
- Bi-weekly 1-on-1 technical mentorship calls
- Personalized GitHub engineering portfolio setup
- Direct entry to Global Demo Day competition
- ML Engineer mentor feedback on all projects
Premium Track
The Ivy Elite Fellowship
₦139,750
/ month · 12 Months
Total: ₦1,677,000 · Programme Duration: 12 Months
- Everything in the Young Architect Track
- Year-round personal guidance from Tolulope Oyejide
- Bespoke AI research project for university admission
- Publication-ready portfolio tailored for Ivy League / Russell Group
- Direct letters of recommendation for top tech programs
Your Child's Mentor
Learning from a Practitioner, Not a Presenter
The quality of the mentor is the quality of the outcome. Tolulope Oyejide is not a career trainer, he is an active Senior ML Engineer and AI Strategist who has built and shipped production AI systems.
TO
Tolulope Oyejide
Founder & CEO, TOL · Senior ML Engineer
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Production ML Systems Builder Engineered and deployed production-grade ML systems including ForecastX (90% accuracy sales forecasting), RiskIQ (loan default prediction), and a customer churn prediction API.
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MBA · AI Department Founder Holds an MBA and previously founded and led an enterprise AI department, delivering AI products at organizational scale.
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Built for the African Context Every project and dataset in this programme is grounded in African economic realities , giving students work that is globally rigorous and locally relevant.
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CEO, Tolulope Oyejide Limited (TOL) TOL is an AI strategy, engineering, and education company operating across corporate clients, executive education, and youth development programmes in Nigeria.
▶ Watch a sample 1-on-1 mentorship session
Common Questions
What Parents Ask
Does my child need any prior programming experience?
No. The programme starts from absolute zero, basic Python syntax and builds systematically. A curious teenager with a working laptop is the only prerequisite.
Is this online, in-person, or hybrid?
Labs are delivered live via video call, making them accessible to students across Lagos and West Africa. Core Track and above include 1-on-1 sessions that are also virtual.
How many hours per week does this require?
Approximately 6–8 hours per week, structured live sessions plus independent homework. It is intensive by design; this is an engineering programme, not a hobby class.
What does the capstone project actually look like?
Students build a complete, deployed ML model on a real dataset, examples include a Lagos property price predictor or a skin-condition classifier. The finished project is hosted on GitHub and presented at Demo Day.
How does the Ivy Elite Fellowship help with university admissions?
The Fellowship produces a publication-ready AI research project specifically crafted to strengthen an application to Ivy League or Russell Group universities, paired with direct letters of recommendation from Tolulope Oyejide.
When does the next cohort begin?
Cohorts are limited in size to preserve mentorship quality. Contact us to join the interest list and be notified of the next opening date.
How Enrolment Works
Start With the Assessment
Before we accept any student, we assess fit. The AI Engineering Career Readiness Assessment takes 10–15 minutes and is completed by your child, with your guidance. Results are sent to both of you.
01
Parent Initiates
You share the assessment link with your child and advise them to complete it honestly, it measures curiosity and logical thinking, not prior knowledge.
02
Child Completes Assessment
Your child fills in the 10–15 min Google Form. Results and a personalised readiness report are automatically emailed to both parent and child.
03
Track Recommendation
Based on the results, you receive a recommended programme track (Entry, Core, or Ivy Elite) with a payment link and enrolment instructions within 24 hours.
04
Payment & Enrolment
Confirm your track, complete the first instalment, and your child is allocated a cohort seat. Placement are capped payment, secures the spot.
A note to parents: Please share the assessment link directly with your child and ask them to complete it themselves, in their own words. The assessment is designed to surface genuine interest and aptitude, not coached answers. Both you and your child will receive the results report by email, so you can review it together.
Begin the Application
Is Your Child Ready to Build AI?
The assessment takes 10–15 minutes. Results are sent to both parent and child. Enrolment follows from there, no phone call required to get started.