Stop Building RAG Prototypes.
Start Shipping Production RAG.
The only Instructor-led Live 8-week course that takes you from a basic Software professional to an AI Engineer ready for Big Tech Companies.
5/5 from all participants
4 hrs/wk
2h theory + 2h hands-on coding
Zero Notebooks
Production-ready templates
Live Q&A
Direct instructor access
🔒 No obligation. Waitlist members get first access + early-bird pricing.
Stuck in RAG Prototype Purgatory?
You built a RAG demo. It worked great in testing. Then reality hit.
Retrieval quality degrades on real queries
Hybrid search & cross-encoder reranking that actually works in production
No way to measure if your RAG is actually good
Evaluation pipelines with faithfulness, recall & relevancy metrics
Latency and costs spiral out of control at scale
Semantic caching & MLOps practices that cut costs by 60%+
This course was built specifically to bridge the gap between "it works in demos" and "it works in production."
THE CAPABILITY GAP
Week 1 vs. Week 8
The Amateur Setup
Stack: Jupyter Notebooks
Retrieval: Basic Vector Search
Data: Naive Character Splitting
Eval: Manual / Vibes
Logic: Linear Chain
The Architect Setup
Stack: Async Microservices on Cloud Run
Retrieval: Hybrid Search + Cross-Encoder Re-ranking
Data: Multimodal Parsing and Semantic Chunking
Eval: Automated Ragas Scores & Guardrails
Logic: Agentic Loops with Self-Correction
Result:Lower Latency, 50% Less Cost, Measurable Accuracy.
The Course Toolkit
Technical Stack Summary
Orchestration
- LangGraph
- Python
- Docker
Database & Storage
- Qdrant
- Weaviate
Ingestion & Parse
- GPT-4o
- ColPali
- Unstructured
Retrieve & Rank
- BM25
- Cross-Encoders (BGE)
- Tavily (Search)
Eval & Observe
- Ragas
- Arize Phoenix
- OpenTelemetry
- NeMo Guardrails
Infrastructure
- FastAPI
- Google Cloud Run
- Gemini Flash
The 8-Week Advanced-RAG Architecture
A unified, visual blueprint of the production-grade RAG pipeline you will build.
What You'll Walk Away With
Concrete skills, not just theory. Every week ends with production-ready code you can use immediately.
Move from RAG POC to production-ready systems in 8 weeks
Implement hybrid search, reranking, and semantic caching
Build evaluation frameworks that catch failures before they reach users
Reduce retrieval latency and LLM costs through production-grade MLOps
Design Agentic RAG patterns that reason over complex, multi-step queries
Walk away with a portfolio of hands-on code ready to deploy
Rated by Real Practitioners
% of cohort 1 participants who rated each topic as extremely valuable
Learn from Practitioners, Not Just Educators
Your instructors have built and shipped RAG systems in production — they teach from hard-won experience, not textbooks.
Ram Seshadri
AI Technical Solutions Architect, Big Tech
Creator of AutoViz · 5.5M+ Downloads
Ram is a senior-level AI Technical Solutions Architect at a Big Tech company and a prominent figure in the Python data science community. With over two decades of hands-on experience, he is best known for creating widely-used open-source Python libraries — including AutoViz (5.5M+ downloads) — that automate complex machine learning tasks. His real-world production expertise grounds every module of this course.
Cornellius Yudha Wijaya
CPO, ARIF Analytics
5.4K followers · 2.6M+ Views
Cornellius is a Data Scientist, AI Engineer, and prolific technical writer with 6+ years of experience building data-driven SaaS products and Generative AI (LLM) solutions. As Chief Product Officer at ARIF Analytics, he bridges the gap between cutting-edge AI research and production-grade applications — bringing a rare mix of depth and accessibility to every lesson.
"We built this course because we kept seeing the same painful pattern: brilliant engineers spending months re-discovering lessons the RAG community already learned the hard way. This course is our way of compressing 2+ years of production experience into 8 focused weeks — so you can skip straight to building great systems."
— Ram & Cornellius, Course Instructors
Is This Course For You?
This is an advanced, practitioner-focused program. It's intentionally not for everyone.
You'll thrive here if you're a...
- Software Engineer building GenAI features in production
- Data Scientist moving beyond notebook experiments to deployed systems
- ML Engineer responsible for LLM infrastructure and retrieval quality
- Technical Lead evaluating RAG architectures for your organization
- AI Product Manager who wants to have informed technical conversations
⚠️ This may not be the right fit if you...
- ✕Have never worked with Python or LLM APIs
- ✕Are looking for a beginner introduction to AI or machine learning
- ✕Want a self-paced course with no live interaction or community
- ✕Are purely a business leader with no hands-on technical role
What Cohort 1 Participants Say
Real feedback from engineers and technical leaders who completed the program.
“The Advanced-RAG course is the ultimate masterclass for bridging the gap between AI prototypes and scalable enterprise products. The curriculum shifts the focus from simple plumbing to strategic LLM refining—tackling the hardest production problems like holistic evaluation metrics, defensive architecture, and optimizing the cost equation through semantic caching and precision reranking. An absolute must-take for anyone looking to build production-ready AI!”
Director, AI Product Management
Fortune 500 Tech Company · Cohort 1
“The Advanced RAG course gave me a much clearer understanding of how RAG systems work beyond the basics—especially around architecture choices, retrieval strategies, evaluation, chunking, embeddings, reranking, and practical trade-offs in production settings. The course helped me think more critically about building reliable GenAI applications.”
Solution Architect
Enterprise Software · Cohort 1
“Fantastic course with immense practitioner insights. Course had zero fluff and had both breadth and depth across the practical aspects of RAG. The architecture frameworks provided gave me tools to assess key bottlenecks in our production pipeline immediately. I strongly recommend this course to everyone interested in RAG.”
Data Engineer
AI-First Startup · Cohort 1
“Excellent teaching on a VERY important topic. What separates this from other RAG content is the production focus—the instructors clearly have first-hand experience shipping systems at scale, not just teaching theory. I recommend this course for everyone using RAGs and Agentic AI.”
Director of Engineering
Healthcare Tech · Cohort 1
“Strong coverage of practical and advanced RAG concepts with a great balance between theory and real-world application. Helpful discussion of architecture patterns and trade-offs. Content was immediately applicable for engineers building production AI systems—I deployed improvements the week after completing the course.”
Senior ML Engineer
Global Financial Services · Cohort 1
8-Week Production RAG Curriculum
From foundational architecture to advanced Agentic RAG — every week builds directly on the last, with hands-on code you ship.
Foundational RAG Architecture & Baselines
- ▸The Naive RAG Baseline
- ▸Understanding retrieval and generation components
Context Aggregation & Chunking Strategies
- ▸Chunking & Embedding
- ▸Multimodal Embedding Models
- ▸Advanced chunking
Improving-Recall Retrieval: Hybrid Search
- ▸Dense & Sparse Indexing
- ▸Implementing Hybrid Search (BM25/SPLADE with vector search)
Enhancing Precision: Re-ranking
- ▸Cross-Encoder Optimization
- ▸Re-ranker implementation
- ▸Metadata filters
Adding Evals & Proactive Guardrails
- ▸Offline & Online evaluation
- ▸Faithfulness, Context Recall, Answer Relevancy
- ▸PII/Toxicity Guardrails
MLOps: Deploying, Performance, Latency & Cost
- ▸Caching strategies
- ▸Semantic Caching
- ▸Managing latency and inference costs
Complex Reasoning & Agentic RAG
- ▸Tool Use & Orchestration Patterns
- ▸Advanced Agentic RAG patterns
- ▸Self-reflection and planning
Observability and A/B Testing
- ▸MLOps for RAG
- ▸Observability setup
- ▸A/B Testing
- ▸CI/CD for LLM applications
4–6 hrs/week
Live session + exercises
8 Code Notebooks
Production-ready templates
Live Q&A
Direct instructor access
💼
Get Reimbursed by Your Employer
Most participants expense this course through their company's L&D budget. Join the waitlist and we'll send you a ready-to-send reimbursement email template for your manager.
Get Reimbursement TemplateJoin the Next Cohort Waitlist
Cohort 1 is complete. Waitlist members get first access when we open registration — plus exclusive early-bird pricing.
Frequently Asked Questions
Everything you need to know before joining the waitlist.
Still have questions?
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Your RAG System Deserves to Be in Production — Not Just a Demo.
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