Shape the cohort
before it begins.
Enroll by May 10. Get more than a price cut, get a seat at the table.
Software engineers who commit early aren't just saving US$210. On Friday, May 15 - about a week before Cohort 2 starts, Dhaval and the team host a private live session for Inner Circle members.
You tell us what you need: the tools you work with, the AI problems you're stuck on, the gaps in your current stack. We listen. Then we curate the weekend deep-dives, case studies, and capstone directions around what you asked for.

Dhaval Patel
1.5M+ YouTube subscribers · 684K+ learners · 17+ years of experience in AI & data.
Teaches the core Build modules: LLM fundamentals, RAG, multi-agent systems, AI system design, and the capstone project.

Hemanand Vadivel
10+ years in analytics and leadership · Built and scaled teams across international markets at Edgewell
Teaches the Orchestrate and Distribute modules: productivity systems, stakeholder management, LinkedIn strategy, and personal branding.

Siddhant Pandey
5+ Years of experience in AI & OpenSource. Hands-on AI Engineer building production systems daily.
Leads live weekend cohorts and practice labs: hands-on coding, project walkthroughs, debugging, and real-time problem solving.
Software engineers who ship real code.
No ML background needed. Just coding experience, curiosity, and drive.
Career Transitioners
Software engineers moving into AI roles with proof.
AI Integrators
Developers adding AI capabilities to existing products.
Tech Leaders
Leads and architects designing AI systems at scale.
Prerequisites
This is not a beginner course. We skip the basics so you can focus on building real AI systems.
Build. Orchestrate. Distribute.
Most bootcamps only teach you to build. We teach all three.
Build
LLMs, RAG, agents, MLOps. The full technical stack.
Orchestrate
Productivity, stakeholders.
Good → great.
Distribute
LinkedIn, GitHub, portfolio. Be visible.
Watch. Build. Practice. Ship.
Designed for working professionals.
Watch
Self-paced videos
Build
Weekend live cohorts
Practice
Labs & exercises
Ship
Deploy to production
12 modules. 75 days.
From LLM foundations to cloud deployment, soft skills to
personal branding.
- Welcome & team introductions
- Cohort roadmap & learning flow
- Dev setup: GitHub, Colab, Claude
- AI Engineering 2026 market trends
- AI landscape
- Python fundamentals & OOP
- REST APIs, FastAPI & LLM Integration
- Layers of AI Engineering stack
- Large Language Models: attention, tokens & context windows
- Embeddings & semantic similarity
- Vector databases with Qdrant
- Model economics & selection
- RAG pipeline & ingestion flow
- LangChain + LCEL basics
- Hybrid search: Vector + BM25
- RAGAS & evaluation metrics
- ReAct agent from scratch
- Tool calling & reasoning loop
- Memory systems for agents
- Reliability caveats in production
- Workflow state machines
- Conditional branches & loops
- Routing, guardrails & compliance (HIPAA, GDPR)
- Trajectory evaluations
- Traces, runs & structured feedback
- Eval datasets & monitoring
- Debug deployed AI systems
- Deploy apps to AWS
- Offline / online eval systems
- Human-in-the-loop review
- Acute risk vs chronic drift
- Beyond RAG agent evals
- MCP fundamentals
- Build MCP servers in Python
- Connect tools, APIs & data
- AI interoperability standards
- Four pillars mastery
- Context compression methods
- Sliding window management
- Prompt caching hands-on
- Multi-agent architectures
- Subgraphs & parallel execution
- Circuit breakers & fallbacks
- Workflow architecture design
- Extract data from PDFs/images
- Multimodal RAG systems
- Image + text retrieval
- Video understanding agents
- LinkedIn positioning
- GitHub portfolio storytelling
- Text-2-SQL architecture
- Self-correcting SQL agents
- Qwen, Gemma, Phi models
- Ollama, vLLM, llama.cpp
- Local deployment patterns
- Build local AI API endpoint
- Protect focused time
- Reduce context switching
- Production AI failures & lessons
- Architecture tradeoff analysis
- Real-time voice stack (Deepgram STT, TTS, LiveKit)
- Low-latency voice systems
- Interruptions & silence handling
- Multi-turn context recovery
- Cost optimization at scale
- Semantic caching systems
- Smart model routing
- Fine-tune vs RAG decisions
- LoRA & QLoRA training
- Data filtering & deduplication
- Synthetic dataset pipelines
- GRPO behind DeepSeek-R1
- Reward design for agents
- Identify true AI use-cases
- Product success metrics
- Prompt injection attacks
- Hallucination drift risks
- Context poisoning defense
- Sandboxed tool execution
- Build complete AI product
- End-to-end system showcase
- Production-ready architecture
- Final polish & review
- Present capstone to panel
- AI system design interviews
- Portfolio review feedback
- Live demo & critique
We update about 20% of the curriculum regularly to keep pace with how the AI industry is moving.
The earlier you join, the less you pay.
One cohort. One bootcamp. Two pricing windows.
Included: Gen AI & DS Bootcamp (US$291 value)
Every new enrollment includes full access to the Gen AI & Data Science Bootcamp 3.0: With Practical Job Placement Support & Virtual Internship at no extra cost. You get both bootcamps for the price of one.
Already own the Gen AI & DS Bootcamp?
You only pay the difference. Your investment of US$291 is fully adjusted — so you pay just US$339 for this bootcamp. Get your adjusted pricing →
No Questions Asked Refund Policy
Enroll with zero risk. Experience the first week of the cohort. If it's not the right fit, request a full refund before May 30. 100% money back, no questions asked.
About Subscriptions
This bootcamp may require a Claude or Codex subscription for your development work. These are separate subscriptions that typically cost $20-$100/month. Please factor this in when making your decision.
Need more details?
Get the full curriculum breakdown or speak with someone from our team.
Questions?
Do I need ML experience?
What is the Inner Circle, and how is it different from regular enrollment?
Do I also get the Gen AI & DS Bootcamp?
When are the live sessions?
When does Cohort 2 officially launch?
What if I miss a live session?
What happens after the 75 days? Do I lose access?
When do I get access after enrolling as an Inner Circle member?
I'm a fresher or have less than 2 years of experience. Can I join?
Who is this bootcamp designed for?
How do I get help if I'm stuck?
Is there job assistance?
What is the Inner Circle price and when does it close?
I already own the Gen AI & DS Bootcamp. What do I pay?
Can I purchase only the AI Engineering Bootcamp without the Gen AI & Data Science Bootcamp?
What's the refund policy for Inner Circle members?
What's the refund policy for Cohort 2 post-launch enrollees?
I used a subsidy (my existing Gen AI Bootcamp or individual course purchase). Can I refund my original purchase after enrolling?
I used a subsidy and now want to refund the AI Engineering Bootcamp itself. What happens?
What system configuration do I need?
• OS: Windows 11
• Processor: Intel Core i7 (10th Gen+) or AMD Ryzen 7 (4th Gen+). An i5 works if you're not focused on local model training.
• RAM: 8GB minimum, 16GB recommended
• Storage: 512GB SSD strongly recommended
• GPU: NVIDIA GTX 1660 or higher for deep learning and GPU-accelerated tasks
This covers all bootcamp work comfortably. You'd only need stronger hardware if you plan to fine-tune small LLMs locally.
What happens on May 15th for Inner Circle members?
The best time was yesterday.
The second best is now.
500 seats · Cohort 2 begins May 24, 2026 · Inner Circle closes May 10