Software engineers & developers
For developers who want to move beyond coding and learn how to build complete AI-powered products.
Magnimind Academy | 15-week mentor-guided program
Become an AI Product Engineer.Learn the technology. Understand the customer. Build the product. Launch it.
AI is changing how products are conceived, built, and launched. This program combines modern AI engineering, product management, entrepreneurship, marketing, and business development into one mentor-guided experience — from AI fundamentals to a working AI product.
- 15 weeks
- Two learning tracks
- Expert mentorship
- AI Product Studio
Learn → Practice → Build → Validate → Launch
Your 15-week AI product journey
Weeks 1–9
AI Product Academy
AI Engineering
Product & Entrepreneurship
Two parallel tracks, every week.
Weeks 10–15
AI Product Studio
Mentor-guided product development, end to end.
Final outcome
Working AI product + product case study + demo
Why this program exists
AI has changed what it means to build a product
- Traditional roles are converging.
- Engineers increasingly need product judgment.
- Product managers increasingly need technical AI fluency.
- Entrepreneurs can now build sophisticated products with dramatically smaller teams.
- AI professionals need to understand not only models and prompts, but also users, interfaces, economics, distribution, and business strategy.
The goal isn't simply to learn AI. The goal is to learn how to turn AI into useful products.
Understand AI
Models, prompts, retrieval, agents — what they can and cannot do.
Build technology
Applications, APIs, data, deployment — with AI-assisted coding.
Think like a product leader
Customers, scope, interfaces, priorities, trade-offs.
Understand the business
Economics, pricing, positioning, distribution, growth.
Who it's for
Built for the new generation of AI professionals
Product managers
For product professionals who want enough technical AI knowledge to understand LLMs, agents, APIs, prototypes, and modern AI product architecture.
Data scientists & analysts
For technical professionals who want to expand from models and analytics into complete AI applications and products.
Entrepreneurs & future founders
For people who want to identify AI opportunities, validate ideas, build MVPs, understand customers, and launch AI businesses.
Career changers & business professionals
For ambitious professionals who want practical AI product skills rather than simply learning AI theory.
Phase 1 · Weeks 1–9
Two tracks. One AI product builder.
During the first nine weeks, students progress through two complementary learning tracks in parallel.
Track A
AI Engineering & Product Development
- LLM fundamentals
- Prompt and context engineering
- Model APIs
- Structured outputs
- Tool / function calling
- RAG
- Embeddings
- Vector databases
- AI agents
- Agentic workflows
- AI automation
- Web development
- Frontend / backend fundamentals
- APIs
- Databases
- Authentication
- AI-assisted coding
- Application deployment
- AI evaluation
- Reliability
- AI product architecture
Track B
AI Product, Business & Entrepreneurship
- AI opportunity discovery
- Customer problems
- Customer discovery
- Personas
- Jobs-to-be-done
- Market research
- Competitive analysis
- Product strategy
- MVP definition
- Product requirements & PRDs
- User experience
- Business models
- AI economics
- Pricing
- Positioning
- Marketing
- SEO fundamentals
- Customer acquisition
- Sales
- Business development
- Go-to-market strategy
- Product analytics
- Launch strategy
Detailed curriculum
The 9-week dual-track curriculum
Each week pairs product and business work with AI engineering, and ends in a concrete outcome.
Mini-capstone
You don't wait until week 10 to start building.
During weeks 1–9, students continuously develop an AI product concept.
- 01Week 1Product idea
- 02Week 2Customer & problem
- 03Week 3PRD + prototype
- 04Week 4Agent / AI workflow
- 05Week 5Product interface
- 06Week 6Deployed prototype
- 07Week 7Marketing & acquisition
- 08Week 8Pricing & GTM
- 09Week 9Mini-capstone presentation
Every major concept in the program is connected to something you are actually building.
The learning platform
More than video lessons
A structured learning system designed for active learning. You study asynchronously through the Magnimind platform while practising and being assessed continuously.
Short, focused lessons
Concise videos and explanations designed around practical concepts.
Hundreds of questions
Frequent knowledge checks, scenario questions, and assessments reinforce understanding.
Coding labs
Students build LLM applications, RAG systems, agents, APIs, and web applications.
Business cases
Students make realistic product, customer, pricing, marketing, and strategy decisions.
Weekly deliverables
Every week produces something tangible.
Assessments
Students demonstrate mastery instead of simply completing videos.
AI-assisted learning
Interactive AI support helps students understand difficult concepts and practice.
Mentor feedback
Human mentors provide deeper feedback on technical decisions, products, and progress.
Mentorship model
Self-paced learning. Human mentorship.
The platform teaches. Mentors guide, challenge, review, and unblock — providing the context, accountability, feedback, and judgment self-paced courses cannot provide alone.
Live mentor sessions
Regular sessions for deeper concepts, problem solving, Q&A, and discussion.
Product clinics
Small-group sessions focused on what students are actually building.
Technical guidance
Help with architecture, coding challenges, LLM applications, agents, and deployment.
Product & business feedback
Mentors challenge assumptions around customers, positioning, product strategy, and go-to-market.
Individual reviews
Scheduled checkpoints provide personalized feedback on progress and direction.
Office hours
Additional opportunities to ask questions and overcome blockers.
You learn independently, but you are not learning alone.
Weekly rhythm
What does a typical week look like?
- 1LearnComplete structured lessons through the Magnimind learning platform.
- 2PracticeAnswer questions, complete exercises, analyze cases, and work through coding labs.
- 3TestComplete quizzes and assessments to identify gaps.
- 4BuildApply the week's concepts to a practical product deliverable.
- 5Meet your mentorsDiscuss challenges, receive feedback, review decisions, and plan the next iteration.
- 6ImproveUse mentor and assessment feedback to strengthen your understanding and product.
Then repeat.
Assessment & accountability
Progress you can measure
Completion is based on demonstrated progress, not simply watching content. Students should demonstrate readiness before progressing into the six-week AI Product Studio. If additional preparation is needed, mentors can recommend targeted remediation and extra practice.
- Knowledge assessments
- 25%
- Technical labs
- 25%
- Product & business assignments
- 20%
- AI Product Mini-Capstone
- 20%
- Mentor evaluation
- 10%
Phase 2 · Now the learning becomes building
6-Week AI Product Studio
Take an AI product from concept to working product. After the nine-week foundation, students enter a mentor-guided product development environment where technical, product, and business skills come together. This is not an internship.
Week 10
Discover & validate
- Problem validation
- Customer definition
- User research
- Product scope
- PRD
- Technical architecture
- Success metrics
Milestone: Product review
Week 11
MVP sprint I
- Product interface
- Backend
- AI integration
- Database
- Core workflow
Milestone: Functional MVP foundation
Week 12
MVP sprint II
- Agents / RAG where appropriate
- Authentication
- Integrations
- Improved UX
- Analytics
- Evaluation
Milestone: Working alpha
Week 13
Test & iterate
- Recruit testers where practical
- Collect feedback
- Identify failure cases
- Evaluate AI quality
- Analyze user behavior
- Iterate on the product
Milestone: Validated product iteration
Week 14
Launch & grow
- Landing page
- Product positioning
- Demo
- Marketing content
- Outreach strategy
- Growth experiment
- Analytics
Milestone: Product launch
Week 15
Demo Day
- Problem → customer → market → product → technology
- Demo → validation → business model
- Growth strategy → roadmap
Milestone: Final AI product presentation
Expected program outputs
Finish with more than a certificate
Students may finish with the following, depending on the nature of their project:
- A working AI product
- Deployed product or functional prototype
- Product case study
- Product requirements document
- Technical architecture overview
- Go-to-market strategy
- Product demo
- Portfolio-ready project
- Resume-ready project description
- Demo Day presentation
- Certificate in AI Product Engineering & Innovation
Emphasis
One program. Two professional directions.
Students study both technology and business, but can emphasize one direction based on their background and goals. These are career directions, not job-placement promises.
AI Product Engineer
Ideal for technically oriented participants.
70% engineering · 30% product & business
Focus
- LLM applications
- Agents
- RAG
- Web development
- AI architecture
- Deployment
- Product thinking
- Customer understanding
Potential career relevance
- AI Product Engineer
- Applied AI Engineer
- AI Application Developer
- AI Solutions Engineer
- AI Automation Engineer
- Technical Product Builder
AI Product Manager & Entrepreneur
Ideal for product, business, founder, and less engineering-intensive backgrounds.
40% engineering · 60% product & business
Focus
- AI technical fluency
- Prototyping
- Product management
- Customer discovery
- Business models
- Marketing
- Go-to-market
- Business development
- Entrepreneurship
Potential career relevance
- AI Product Manager
- Technical Product Manager
- AI Product Strategist
- AI Solutions Consultant
- Entrepreneur / Founder
- AI Business Innovation roles
Skill pillars
Six pillars, one product builder
AI
- LLMs
- RAG
- Agents
- Automation
- Multimodal AI
Build
- Web applications
- APIs
- Databases
- Deployment
- AI-assisted coding
Product
- Customer discovery
- PRDs
- UX
- MVP
- Product analytics
Business
- Market research
- Business models
- Pricing
- Business development
Grow
- Positioning
- Marketing
- SEO
- Sales
- Go-to-market
Ship
- AI Product Studio
- User feedback
- Iteration
- Launch
- Demo Day
Time commitment
Designed for working professionals. Built for serious progress.
Expect a meaningful weekly commitment across asynchronous learning, assessments, coding and product assignments, mentor sessions, and product development. The self-paced component provides scheduling flexibility, while weekly milestones create accountability.
How this differs
Program comparison
Traditional online course
- Watch lessons
- Complete quizzes
- Mostly self-directed
- Limited personalized feedback
Coding bootcamp
- Primarily technical
- Coding-heavy
- Often focused on one role
- Limited business training
Magnimind AI Product Engineer Program
- AI engineering
- Product management
- Entrepreneurship
- Marketing & GTM
- Continuous assessments
- Human mentorship
- AI Product Studio
- Portfolio-ready product
Choose your path
How this compares to our data science programs
The AI Product Engineer program sits alongside — not instead of — our data science programs. Pick the one that matches what you want to be doing next year.
New flagship
AI Product Engineer & Innovation
- Best for
- Building and launching AI products end to end
- Length
- 15 weeks (9-week academy + 6-week product studio)
- Core focus
- AI engineering + product, business, and go-to-market
- You build
- A working AI product, case study, and demo
- Business & GTM training
- Yes — product management, pricing, positioning, launch
- Mentorship
- Weekly mentor sessions plus studio guidance
- Tuition
- $7,000
Data science career path
Mentor-Led Data Science & AI Program
- Best for
- Moving into a data science, ML, or AI role
- Length
- 24 weeks full track, or 15-week accelerated
- Core focus
- ML, NLP, deep learning, and an industry project
- You build
- A portfolio of mentor-reviewed industry projects
- Business & GTM training
- Light — career and interview preparation
- Mentorship
- 1:1 mentorship in small cohorts
- Tuition
- $6,000 – $9,000 depending on track
Focused deep dive
LLM & AI Agent Bootcamp
- Best for
- Going deep on LLM and agent engineering
- Length
- Short, focused cohort
- Core focus
- LLM APIs, RAG, and agentic systems
- You build
- Hands-on LLM and agent projects
- Business & GTM training
- No — technical focus
- Mentorship
- Instructor-led sessions
- Tuition
- See bootcamp site
Career development
Build the product. Learn to present your value.
Career preparation is built around your actual AI Product Studio work — the product you built, the decisions you made, and the results you can show.
- Resume feedback
- LinkedIn / profile positioning
- Project storytelling
- Portfolio presentation
- Technical interview preparation
- Product interview preparation
- Demo preparation
- Career strategy
- Professional communication
Certificate
Certificate in AI Product Engineering & Innovation
Students who successfully satisfy the program's completion requirements receive a Magnimind Academy Certificate in AI Product Engineering & Innovation — awarded for demonstrated learning, product development, and successful program completion.
Tuition
AI Product Engineer & Innovation Program
15 Weeks
$7,000
Payment plans, financing, and cohort dates are published on our payment options page and confirmed during your application call.
What's included
- 9-week dual-track AI Product Academy
- 6-week AI Product Studio
- AI Engineering curriculum
- Product & Entrepreneurship curriculum
- Interactive assessments
- Technical labs
- Product / business assignments
- Mini-capstone
- Live mentorship
- Product clinics
- Mentor feedback
- Office hours where scheduled
- Learning platform access
- AI-assisted learning support where available
- Career preparation
- Demo Day
- Certificate upon successful completion
Stories
What participants say
Real stories from people who moved from building models and features to shipping AI products.
We publish stories only once the person behind them approves the wording. Be the first to share yours — approved stories appear here.
Share your story
Alumni and current participants: tell us what you built and what changed. Our team reviews every submission before publishing.
Cohort notifications
Join the waitlist for the next cohort
Cohorts are small and seats go quickly. Add your name and we'll email you as soon as the next AI Product Engineer & Innovation Program cohort opens — dates, deadlines, and the application window, nothing else.
- First notice when applications open
- Cohort dates and tuition deadlines
- Invitations to info sessions and studio demos
Ready now? Register for the current cohort.
FAQ
Questions people ask first
Keep exploring
Other ways into AI at Magnimind
Mentor-Led Data Science & AI ProgramIf you want a data science career path with an industry project.LLM & AI Agent BootcampA focused deep dive into agentic LLM engineering.Live info sessionsMeet mentors and ask about the AI Product Studio.AI articles and tutorialsRead how our mentors think about LLMs, RAG, and agents.
Don't just learn AI. Build with it.
The future belongs to professionals who can connect AI technology with real customer problems and turn ideas into useful products. Spend 15 weeks learning how to think, build, validate, and launch like an AI product professional.
Applications are reviewed to ensure the program is appropriate for each participant's background and goals.