Track 1
Software Engineers
Add GenAI to your stack and ship intelligent product features in production.
Master Generative AIBy Building Real SystemsLLMs, RAG & AI Agents
Build production-ready AI systems the way real AI engineers do - not toy demos.
Python, OOP & Core Libraries
for AI Systems
Production APIs with FastAPI
Real backend architecture
OpenAI & Gemini via SDKs
Unified with LangChain
RAG Pipelines
Embeddings & Vector Search
Trusted by 2,000+ engineers from startups & product companies
12+ Real AI Projects
Resume-Ready Portfolio
Lifetime Access
Community & Mentorship
Why This Course?
Most AI courses teach you to call OpenAI APIs. We teach you to build systems that scale.
Traditional Courses
Outdated approach
- Courses filled with theory, zero production code
- No understanding of RAG or Agent architectures
- Can't deploy models to production
- Missing modern tools like LangChain, Vector DBs
VS
VRKA AI Approach
Production-first learning
- Build 10+ production-ready GenAI systems
- Master RAG pipelines and AI Agent design
- Deploy to AWS with Docker and FastAPI
- Use OpenAI, LangChain, Pinecone, and more
What You Will Build?
Not toy examples. Production systems you can put on your resume.
Advanced RAG Pipeline
Build a retrieval-augmented generation system with semantic search, reranking, and citation tracking.
Semantic search with vector embeddings
Intelligent document reranking
Automatic source citation tracking
Context-aware hallucination reduction
LangChainPineconeOpenAIPython
What You Will Learn?
12-week intensive program. Zero fluff. Maximum impact.
Phase 1
Foundations & LLM Basics
2 Weeks
Transformer Architecture
Tokenization Strategies
API Design
Prompt Engineering
Phase 2
Retrieval-Augmented Generation
3 Weeks
Embedding Models
Vector Databases
Hybrid Search
RAG Evaluation
Phase 3
AI Agents & Tools
3 Weeks
ReAct Pattern
Tool Use
Agent Memory
Multi-Agent Systems
Phase 4
Production Deployment
2 Weeks
FastAPI Services
Docker Containers
AWS/GCP Deployment
Scaling Strategies
Phase 5
Advanced Topics
2 Weeks
Fine-tuning LLMs
RLHF Concepts
Safety & Guardrails
Cost Optimization
Who Is This For?
Purpose-built for ambitious builders who want to create real AI products, not demos.
Track 2
Data Engineers
Design vector-ready data pipelines and scalable LLM architecture foundations.
Track 3
CS Students
Build high-signal AI projects that strengthen your portfolio and interview edge.
Track 4
Tech Professionals
Transition into AI product work with practical, role-ready implementation skills.
What Will You Use?
A carefully curated GenAI stack used in real-world production systems.
O
OpenAI
LLM
L
LangChain
Framework
P
Pinecone
Vector DB
P
Python
Language
F
FastAPI
Backend
D
Docker
DevOps
A
AWS
Cloud
H
HuggingFace
Models
G
Git
Version Control
S
Streamlit
Frontend
P
PyTorch
ML Framework
R
Redis
Cache
O
OpenAI
LLM
L
LangChain
Framework
P
Pinecone
Vector DB
P
Python
Language
F
FastAPI
Backend
D
Docker
DevOps
A
AWS
Cloud
H
HuggingFace
Models
G
Git
Version Control
S
Streamlit
Frontend
P
PyTorch
ML Framework
R
Redis
Cache
What Do Our Engineers Say?
Real results from real builders.
"
I went from zero GenAI knowledge to shipping a RAG system for my company in 8 weeks. This course cuts through the noise.
Alex Chen
Senior Engineer at Spotify
What Does It Cost?
One-time enrollment for the complete GenAI program.
Limited Seats
Complete GenAI Program
₹14,999₹29,999
One-time payment · Lifetime access
12-week structured GenAI curriculum
10+ hands-on, production-oriented projects
Weekly live Q&A sessions
Private community access
1-on-1 portfolio review
Certificate of completion
Job and referral network access
Lifetime access to content updates
Enrollment is limited to ensure session quality.
Have Questions?
Questions? We've got answers.