How much theory vs implementation?
Each week pairs core concepts with executable labs so intuition and shipping skills grow together.
COURSE 1 · LIVE MENTORING
From LLM fundamentals to production-ready AI building blocks.
Build real-world AI intuition first, then ship reliable systems with confidence.
Master transformers, prompt engineering, embeddings, RAG, fine-tuning, and evaluation with hands-on weekly deliverables.
Start
Aug 8, 2026
Format
Live sessions + notebooks
Commitment
8 weeks · 4 hours/week
8
Modules
Study Companion App
Capstone
100% project-based
Assessment model
Python + LLM APIs
Primary stack
In This Session
Everything you need to evaluate your next move
Will I work with modern AI tooling?
Yes. You use LangChain, LlamaIndex, embeddings, vector stores, and evaluation frameworks.
Is this relevant for real product teams?
Every project targets practical reliability, cost, and quality outcomes used in production AI systems.
What do I leave with?
A complete capstone that combines RAG, fine-tuning, and evaluation into a deployable assistant.
What You Will Leave With
Practical outcomes, not just theory
- Build robust prompt pipelines and compare strategy performance using measurable criteria.
- Implement semantic retrieval systems with vector databases and grounded response generation.
- Fine-tune domain-adapted models and benchmark improvements over base models.
- Create automated evaluation harnesses for correctness, relevance, and safety.
Certificate
Completion certificate for verified track milestones.
Capstone Project
Build and present a portfolio-ready final implementation.
Practical Labs
Hands-on exercises focused on real engineering workflows.
Assessments
Project-based evaluation with actionable instructor feedback.
Curriculum roadmap
Cohort Track
Part 1
Week 1 - LLM Foundations
Tokenization, attention, and transformer intuition for builders.
Part 2
Week 2 - Prompt Engineering
Zero-shot, few-shot, chain-of-thought, and template systems.
Part 3
Week 3 - AI APIs at Scale
Retries, rate limits, streaming, and cost-aware API wrappers.
Part 4
Week 4 - Embeddings + Vector Search
Indexing and retrieval with ranking quality controls.
Part 5
Week 5 - RAG Engineering
Grounded QA pipelines with source-aware generation.
Part 6
Week 6 - Fine-Tuning
Domain adaptation using practical data and LoRA workflows.
Part 7
Week 7 - Evaluation Systems
Automated eval loops and quality scorecards.
Part 8
Week 8 - Capstone
AI-powered study companion with full-stack integration.
Live Calendar
AI Foundations Schedule by Date
Saturday and Sunday · 11:00 AM PST · 2 hours/session
Add All Sessions to CalendarSaturday
Sat, Aug 8, 2026
Upcoming
Week 1 - LLM Foundations
Tokenization, attention, and transformer intuition for builders.
11:00 AM PST · Upcoming
Sunday
Sun, Aug 9, 2026
Upcoming
Week 1 - LLM Foundations - Lab and Q&A
Hands-on implementation and feedback for week 1 - llm foundations.
11:00 AM PST · Upcoming
Saturday
Sat, Aug 15, 2026
Upcoming
Week 2 - Prompt Engineering
Zero-shot, few-shot, chain-of-thought, and template systems.
11:00 AM PST · Upcoming
Sunday
Sun, Aug 16, 2026
Upcoming
Week 2 - Prompt Engineering - Lab and Q&A
Hands-on implementation and feedback for week 2 - prompt engineering.
11:00 AM PST · Upcoming
Saturday
Sat, Aug 22, 2026
Upcoming
Week 3 - AI APIs at Scale
Retries, rate limits, streaming, and cost-aware API wrappers.
11:00 AM PST · Upcoming
Sunday
Sun, Aug 23, 2026
Upcoming
Week 3 - AI APIs at Scale - Lab and Q&A
Hands-on implementation and feedback for week 3 - ai apis at scale.
11:00 AM PST · Upcoming
Saturday
Sat, Aug 29, 2026
Upcoming
Week 4 - Embeddings + Vector Search
Indexing and retrieval with ranking quality controls.
11:00 AM PST · Upcoming
Sunday
Sun, Aug 30, 2026
Upcoming
Week 4 - Embeddings + Vector Search - Lab and Q&A
Hands-on implementation and feedback for week 4 - embeddings + vector search.
11:00 AM PST · Upcoming
Saturday
Sat, Sep 5, 2026
Upcoming
Week 5 - RAG Engineering
Grounded QA pipelines with source-aware generation.
11:00 AM PST · Upcoming
Sunday
Sun, Sep 6, 2026
Upcoming
Week 5 - RAG Engineering - Lab and Q&A
Hands-on implementation and feedback for week 5 - rag engineering.
11:00 AM PST · Upcoming
Saturday
Sat, Sep 12, 2026
Upcoming
Week 6 - Fine-Tuning
Domain adaptation using practical data and LoRA workflows.
11:00 AM PST · Upcoming
Sunday
Sun, Sep 13, 2026
Upcoming
Week 6 - Fine-Tuning - Lab and Q&A
Hands-on implementation and feedback for week 6 - fine-tuning.
11:00 AM PST · Upcoming
Saturday
Sat, Sep 19, 2026
Upcoming
Week 7 - Evaluation Systems
Automated eval loops and quality scorecards.
11:00 AM PST · Upcoming
Sunday
Sun, Sep 20, 2026
Upcoming
Week 7 - Evaluation Systems - Lab and Q&A
Hands-on implementation and feedback for week 7 - evaluation systems.
11:00 AM PST · Upcoming
Saturday
Sat, Sep 26, 2026
Upcoming
Week 8 - Capstone
AI-powered study companion with full-stack integration.
11:00 AM PST · Upcoming
Sunday
Sun, Sep 27, 2026
Upcoming
Week 8 - Capstone - Lab and Q&A
Hands-on implementation and feedback for week 8 - capstone.
11:00 AM PST · Upcoming
Inside the learning experience
Every session is built around implementation outcomes. These modules show exactly what you will build, practice, and carry into real projects.
Module 1
Week 1 - LLM Foundations
Tokenization, attention, and transformer intuition for builders.
Module 2
Week 2 - Prompt Engineering
Zero-shot, few-shot, chain-of-thought, and template systems.
Module 3
Week 3 - AI APIs at Scale
Retries, rate limits, streaming, and cost-aware API wrappers.
Module 4
Week 4 - Embeddings + Vector Search
Indexing and retrieval with ranking quality controls.
Module 5
Week 5 - RAG Engineering
Grounded QA pipelines with source-aware generation.
Session Host
Experience
25 years of IT experience across engineering delivery, quality, and modern platform transformation
Focus
AI, Automation, and Production Engineering
Deepak Kamboj
Founder and Lead Instructor
Deepak Kamboj is an AI and quality engineering mentor who helps teams move from tutorial-level learning to production-ready implementation. His teaching style combines architecture clarity, real delivery constraints, and execution patterns that engineers can apply immediately.
- Founder of DevBuild Studio with hands-on focus on modern engineering skills
- Mentors engineers across Playwright automation, agentic AI, and production architecture
- Known for practical frameworks, implementation checklists, and career-focused coaching
Where our learners and teams operate
Mistral
OpenAI
Anthropic
Pinecone
Chroma
LangChain
LlamaIndex
GitHub Actions
Learner outcomes
"This course made embeddings and RAG finally click. I shipped my first internal assistant in week 6."
"Project-based grading pushed me to build real systems, not just complete quizzes."
"The evaluation module changed how I think about AI quality and production readiness."
Frequently asked questions
What are the prerequisites?Open
Python basics, REST API familiarity, and basic command-line comfort are enough.
Are there exams?Open
No exams. The course is fully assessed via labs, projects, and a capstone demo.
Can I use my own dataset?Open
Yes. You are encouraged to tailor labs and capstone work to your target domain.
Final call
Build the skillset teams are prioritizing right now
Reserve your spot and receive your onboarding details, prep material, and implementation roadmap.