Edison AI Academy · Foundations
Generalist AI Bootcamp
Walk in curious about AI. Walk out building with it.
A fast, practical introduction to AI thinking, creative experimentation, and first prototypes for curious students.
- Age range
- 13–18
- Duration
- 4 or 8 weeks
- Format
- On-campus or online
- Level
- Foundation
- Cohort
- 12–16 students
- Outcome
- First AI project + showcase
What is the Generalist AI Bootcamp?
The Generalist AI Bootcamp is Edison AI Academy's entry program: a 4- or 8-week, project-based course for students aged 13–18 with no coding experience. Students learn how AI systems work, how to prompt them with structure, and how to combine AI tools into workflows that solve real problems — finishing with a working AI project they present at a live showcase.
The 8-week track adds an introduction to Python, a first AI API call, and a second self-directed build. It is the fastest, lowest-commitment way for a student to build genuine AI capability — and to find out whether they should continue into Edison's year-long programs.
A hands-on entry point into Edison AI Academy.
A fast, practical introduction to AI thinking, creative experimentation, and first prototypes for curious students.
Four weeks, or eight. That is the whole distance between having heard of ChatGPT and having built, documented, and presented a working AI project.
No prior coding is required. Students learn structured prompting, map the modern AI toolkit across text, image, audio, and research, and chain those tools into workflows that solve a real problem. Every session produces something; every week builds on the last.
The 8-week track adds the first real code — Python, a first AI API call, and a second, more ambitious build. Either way, a student leaves with the first artefact in an Edison portfolio and a clear answer to one question: should they go further?
- What this program is
A hands-on entry point into Edison AI Academy.
- Who it is for
Students beginning their AI journey.
- What students build
A complete project in a compressed format
- What students learn
Students move quickly through Inquiry, Explore, Build, Critique and Exhibit, leaving with one tangible project they can show, explain, and continue developing.
- How students are taught
Small cohorts of 12–16 students, mentor ratio 1 mentor : 6 students. Edison runs on case-based learning, rotating studio roles, prototype-first modules, and closing showcase.
- Final outcome
First AI project + showcase
The Edison Learning Engine
How a program assembles into capability.
Edison programs are not a sequence of lessons. They are a learning engine, six parts that fit together to produce thinkers who can build with AI, defend their work, and lead.
Assembly
- 01
Curiosity Core
Students begin with questions, not templates. They learn to investigate problems before reaching for tools, the genuine intellectual engine of the program.
- 02
AI Fluency Layer
Students learn how to use AI systems as thinking partners, research assistants, and creative collaborators, across prompts, models, tools, and workflows.
- 03
Builder Studio
Students move from ideas into prototypes, turning abstract concepts into tangible AI-powered outputs through structured, hands-on experimentation.
- 04
Systems Thinking Ring
Students learn to see the whole system: users, constraints, incentives, workflows, ethics, and impact, the connective tissue that turns parts into outcomes.
- 05
Communication Lens
Students learn to present their thinking clearly, explain how their solution works, defend their decisions, and refine in response to critique.
- 06
Final Prototype Engine
Every module ends with a working prototype that students can demonstrate, explain, and improve, the assembled output of the entire learning engine.
The learning pathway, term by term.
The bootcamp runs as two tracks. The 4-week Intensive moves from how AI works to a finished showcase. The 8-week Extended adds advanced prompting, the transition into Python, and a second, self-directed build.
- W01
Weeks 1–2
What Intelligence Is
How AI actually works — pattern recognition, language models, next-token prediction. Structured prompting with the Role–Context–Task–Format–Constraints framework, and a clear-eyed look at where AI fails: hallucination, bias, and plain error.
- How LLMs work
- Structured prompting
- Spotting AI failure
- W02
Weeks 2–3
The Tool Landscape
A guided tour of the working toolkit across text, image, audio, research, and data — and the first real skill: chaining several tools into one end-to-end workflow that produces a result no single tool could.
- AI tool fluency
- Multi-tool workflows
- Project scoping
- W03
Weeks 3–4
Make It Real
A full build session with no-code AI tools — custom GPTs, AI app builders, automation — with roaming mentor support and a mid-session troubleshooting circle. Students document their process as they go.
- No-code building
- Automation
- Process documentation
Artefact A working AI-powered project
- W04
Weeks 5–7 · 8-week track
Meet Python
The 8-week track crosses into code. Students write their first Python, make their first call to an AI API, and build a working chatbot in around twenty lines — typing every line themselves.
- Python basics
- AI API calls
- Reading code
- W05
Final week
The Showcase
Studio critique, presentation coaching, and a live showcase — a three-minute presentation with questions, in front of peers and family. The first defence of a first portfolio piece.
- Studio critique
- Presenting
- Defending your work
Artefact Showcase presentation and AI journal
Visible progress, every single week.
The bootcamp is built as a climb. Students arrive curious, leave having shipped, and present the result at a showcase their family is invited to attend.
- 01Arrive
A curious beginner who has used AI but never built anything with it.
- 02Build
A student running multi-tool AI workflows and prototyping a real project with mentor support.
- 03Exhibit
A maker who has shipped, documented, and presented a working AI project to a live audience.
Students learn with the tools modern builders actually use.
The Generalist AI Bootcamp toolkit is curated to match the depth and ambition of this program. Students learn to choose, combine, and switch between tools, not memorise a single platform.
Category
AI Assistants
- ChatGPT
- Claude
- Gemini
Category
Creative Building
- Canva
- Figma
- Lovable
Category
Research
- Perplexity
- NotebookLM
Tools evolve. Edison teaches the durable thinking, choosing the right tool, combining tools well, and switching when a better tool emerges.
Edison AI Academy
Founding faculty
Students learn from instructors who combine AI fluency, curriculum design, strategy, and practical implementation experience. Edison AI Academy is built around the belief that young people do not just need to learn tools, they need to learn how to think, build, and lead with them.
Cohorts are deliberately small (12–16 students, mentor ratio 1 mentor : 6 students), so every student is known, stretched, and held to a high standard.
We teach young people how to think, build, and lead with AI, not just how to use it.
Edison AI Academy is a selective program. Fees reflect the small cohort size, mentor ratio, and the depth of the work students complete.
Flexible payment plans may be available for accepted students. Bursaries and scholarships are reviewed individually as part of the admissions conversation.
We frame this as an investment in your child's future readiness, not a transactional fee for content delivery.
Generalist AI Bootcamp — answers we get asked most.
Not sure if Generalist AI Bootcamp is the right fit?
Speak with Edison AI Academy about your child's goals, current skill level, and best-fit pathway. We will recommend the right program and the next available cohort.
Three short steps. We'll match you to the right Edison pathway.
Our admissions team reviews every application personally and replies within one business day. The form takes about two minutes.
Your Generalist AI Bootcamp preference travels with you to the application form — we'll know exactly what you're interested in.