Build Real AI Projects in 8 Weeks.
2 live sessions/week • 4 mini projects + 1 capstone • GitHub-ready portfolio
Limited seats • Beginner-friendly • Mentor feedback
Ambient neural patterns loading
Instructor
Yuvraj Raina
Industry specialist, mentor, entrepreneur
Yuvraj has guided founders, engineers, and teams to ship AI-powered products. The bootcamp is designed to move you from concepts to real-world builds with disciplined weekly delivery.
Why learn with Yuvraj
- Hands-on mentor with industry delivery experience
- Structured 8-week sprint with weekly outcomes
- Focus on portfolio-ready projects and real-world workflows
Program Highlights
Built for real-world AI builders
Hands-on sessions, weekly deliverables, and a clear portfolio outcome.
Live, practical learning
Two 90-minute live sessions per week with 30 minutes of theory and 60 minutes of coding.
Weekly deliverables
Stay accountable with mini labs, project milestones, and clear feedback loops.
Beginner-friendly
We start from fundamentals and quickly move to modern AI applications.
Real-world outcomes
Graduate with a GitHub-ready portfolio and capstone you can showcase.
Program outcomes
- 4 mini projects (biweekly)
- 1 capstone project
- GitHub portfolio with clean READMEs
- Mentor feedback and review
Who it is for
- Aspiring AI/ML engineers
- Software developers pivoting into AI
- Founders building AI-powered products
- Students aiming for project-based learning
Syllabus
8-week timeline with weekly deliverables
Two sessions per week with a clear deliverable to keep momentum and ship projects.
Search & Problem Solving (Sokoban)
Session 1
- Problem formulation
- State space
- BFS/DFS
Session 2
- Heuristics
- A*
- Implementing solver + experiments
Advanced Search + Optimization
Session 1
- Improving heuristics
- Pruning
- Complexity
- Debugging
Session 2
- Performance profiling
- Clean project structure
- README writing
Supervised Learning Foundations
Session 1
- Data and features
- Train/val/test
- Metrics
- Linear models
Session 2
- Hands-on classifier/regressor notebook
- Evaluation
Practical Supervised ML
Session 1
- Overfitting
- Regularization
- Model selection
- Pipelines
Session 2
- End-to-end mini project
- Dataset selection
- Report writing
Intro to Modern AI Apps
Session 1
- LLM basics
- Prompting
- Structured outputs
Session 2
- Build Mini Project 3
- Simple AI assistant web app
RAG + Knowledge Apps
Session 1
- Embeddings
- Vector DB concepts
- Chunking
Session 2
- Build Mini Project 4
- RAG app with citations
Capstone Build Sprint
Session 1
- Capstone planning
- Architecture
- Milestones
- Git workflow
Session 2
- Build + mentor review
- Debugging
- Evals
Capstone Launch + Portfolio
Session 1
- Deployment
- Polishing
- Demos
- Storytelling
Session 2
- Final presentations
- Portfolio/GitHub cleanup
- Next steps
Projects
Build real AI applications
Every two weeks you ship a project. By the end, your capstone is portfolio ready.
Mini Lab 1: Sokoban Solver
Implement a baseline solver with BFS/DFS and test scenarios.
Mini Project 1: Sokoban Solver v2
Improve heuristics, prune efficiently, and publish a clean GitHub repo.
Mini Lab 2: Supervised Learning Notebook
Build and evaluate a classifier/regressor with clean metrics.
Mini Project 2: End-to-End ML Project
Select a dataset, build a pipeline, and publish a mini report.
Mini Project 3: AI Assistant App
Ship a simple AI assistant web app with structured outputs.
Mini Project 4: RAG App
Build a retrieval app with citations and evaluation notes.
Capstone Project
Define a real-world problem, build, iterate, and publish a polished final demo.
Pricing
Choose your learning tier
Flexible options depending on the level of feedback and support you want.
Starter
9999₹
Best for focused learners who want live guidance.
- Live classes
- Class recordings
- Weekly deliverables
Builder
19999₹
For builders who want faster feedback and support.
- Everything in Starter
- Assignments review
- Priority support
Pro
49999₹
For serious builders who want industry level 1:1 feedback.
- Everything in Builder
- 1:1 feedback
- In depth Capstone review
Limited seats. Pricing may change for next cohort.
FAQ
Answers before you enroll
Do I need prior AI experience?
No. We start from fundamentals and move quickly into modern AI workflows.
What if I miss a live session?
Each class is recorded and shared so you can catch up.
How much time should I allocate weekly?
Plan for 4 to 6 hours per week including classes and project work.
Will I build a portfolio?
Yes. You will complete four mini projects and a capstone with GitHub-ready repos.
Is there feedback on assignments?
Yes, feedback is included in Builder and Pro tiers; Pro includes 1:1 support.
How do I register?
Click Register Now or WhatsApp Us and we will walk you through the next steps.
Register
Ready to Build Your AI Portfolio?
Seats are limited. Secure your spot by contacting Yuvraj directly.
Replies within 24 hours on business days.