RAG AI & Automation
RAG AI & Automation is a 10-week course teaching you to build retrieval-augmented AI systems that ground large language models in real data, using embeddings, vector databases, hybrid search, and re-ranking, then automate multi-step business workflows around them with tools like n8n and LangChain — for Python developers building production AI search and automation.
Learn to build retrieval-augmented AI systems that ground large language models in real data, then automate business workflows around them end to end.
What you'll learn
Course details
Duration
10 weeks
Best for
Developers comfortable with Python who want to build production-grade AI search and automation systems
Enrollment isn't open for this course yet — check back soon or contact us.
Course Curriculum
A module-by-module breakdown of what you'll cover in RAG AI & Automation.
01Getting Started & Environment Setup
4 topicsWeeks 1–2
- Getting API access to Claude or OpenAI
- Installing LangChain and LlamaIndex
- Creating a free Pinecone account (or setting up pgvector)
- Installing n8n via Docker and setting up Langfuse/LangSmith
02Basic
5 topicsWeek 3
- Calling LLM APIs with structured JSON output
- Managing tokens, context windows, and rate limits
- Environment and secrets management
- Python fundamentals for AI engineering
- Event-driven triggers: webhooks, schedules, and polling for RAG automation
03Intermediate
5 topicsWeeks 4–5
- Embedding models and similarity metrics
- Working with Pinecone, Chroma, FAISS, and pgvector
- Index types: HNSW and IVF
- Benchmarking retrieval latency and accuracy
- Incremental index refresh: keeping a RAG knowledge base up to date
04Advanced
5 topicsWeeks 6–7
- Parsing PDFs, HTML, and scanned documents
- Fixed vs. semantic chunking strategies
- Metadata tagging and overlap tuning
- Table and image extraction
- Human-in-the-loop approval gates in automated workflows
05Pro
8 topicsWeek 8
- System prompts for grounded, citation-backed answers
- Few-shot prompting and hallucination guardrails
- Hybrid search combining BM25 and vector retrieval
- Cross-encoder re-ranking and query rewriting
- Building automation workflows with n8n and LangChain/LangGraph
- Scoring faithfulness and relevance with RAGAS, and production deployment
- Orchestrating multi-step business workflows and connecting RAG automation to CRMs
- Dead-letter queues and retry strategies for automation pipelines
06AI Pro
3 topicsWeeks 9–10
- Using Claude, ChatGPT, and Perplexity to design RAG automation workflows
- Verifying AI-designed RAG automation workflows before production use
- Project: Use AI to design an action-taking RAG workflow, then test its failure paths
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
Need this built for your business instead?
If you'd rather have it done than learn it, our solutions team delivers this work for businesses directly.
Real-Time, Industry-Based Projects
This is project-based learning modeled on real industry scenarios — you'll build portfolio-ready work as you go, not just watch lectures.
Every course includes a guided internship on top of your project work — so you graduate with real experience, not just a certificate.
Communication & Soft Skills
Built into every course, alongside the technical curriculum.
Communication Skills
Practice explaining technical work clearly to teammates, managers, and clients.
Practical AI Skills
Hands-on training in using AI tools well — prompting, everyday workflows, and where AI actually helps versus where it doesn't.
Teamwork & Collaboration
Work in small project teams using real workflows like stand-ups and code reviews.
Problem Solving
Build the habit of breaking down ambiguous problems into clear, solvable steps.
Time Management
Learn to plan, prioritize, and deliver project work against realistic deadlines.
Presentation Skills
Present your project work and results with confidence, as you would to a client.
Resume & Profile Building
Build a strong resume, LinkedIn profile, and project portfolio that recruiters notice.
Interview Preparation
Mock interviews and portfolio reviews to get you ready for real job applications.
Career & Placement Support
100% of students enrolled in RAG AI & Automation get full access to placement support — real tools and guidance, not just a promise. This is support and access, not a guaranteed job outcome.
Resume Builder
A resume auto-built from your real completed projects and certificates, ready to export.
Shareable Portfolio
A public portfolio page showcasing your approved projects, with a link you can share with employers.
Interview Preparation
Guidance on presenting your projects and experience clearly in real interviews.
Peer & Mentor Community
Ongoing access to our learner community for questions, feedback, and support after you finish.
What Your Certificates Look Like
Real, verifiable certificates with your name, RAG AI & Automation, and a QR code anyone can scan to confirm they're genuine — one for completing the course, and a separate one if you take the internship track. Earning a certificate is free. To view, download and share it, there's a one-time ₹100 release fee per certificate — the same for free-course, paid-course and internship certificates.
Course Completion Certificate
Data24ZoneCertificate of Completion
Illustrative recipient
Your Name Here
Example certificate for completion of
RAG AI & Automation
- Certificate No.
- D24-SAMPLE
- Mode
- Self-Paced
- Duration
- 10 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Internship Completion Certificate
Data24ZoneCertificate of Internship
Illustrative recipient
Your Name Here
Example certificate for completion of
RAG AI & Automation
- Certificate No.
- D24-SAMPLE
- Mode
- Internship
- Duration
- 10 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Frequently Asked Questions
What will I learn in the RAG AI & Automation course?
You'll learn: Building retrieval pipelines with embeddings and vector databases; Advanced retrieval techniques: hybrid search, re-ranking, and query rewriting; Automating multi-step workflows that combine LLM calls with business systems; Evaluating and deploying RAG systems with production-grade monitoring.
What tools and technologies does the RAG AI & Automation course cover?
This course covers: Claude / OpenAI API, Pinecone / pgvector, LangChain, LlamaIndex, n8n, Cross-encoder rerankers, RAGAS, Langfuse / LangSmith.
Is the RAG AI & Automation course beginner-friendly?
This is a intermediate-level course, so it assumes some prior familiarity with the subject. It starts with a "Getting Started & Environment Setup" module covering tool installation before the main curriculum.
How long does the RAG AI & Automation course take to complete?
The course is designed to be completed in approximately 10 weeks, depending on your pace.
What enrollment options are available for RAG AI & Automation?
Project Training Track (₹1,499) — One defined learning project and 2 review sessions; no employment or stipend included. Self-Paced (₹1,999) — Learn anytime with the full recorded curriculum and community access.
Is there an internship option for RAG AI & Automation?
Yes — the Internship track means working through real projects with our team and earning a separate Internship Certificate.
Will I get a certificate after completing RAG AI & Automation?
Yes. Self-paced enrollment earns a course completion certificate once your final project is reviewed and approved. Internship enrollment earns an internship certificate once your internship projects are approved. Every certificate is publicly verifiable on our website and can be added directly to your LinkedIn profile. Earning it is free; releasing it to view, download and share is a one-time ₹100 fee per certificate.
What kind of projects will I build in RAG AI & Automation?
You'll work on real projects such as: Internal knowledge-base assistant — a retrieval-augmented Q&A tool over company docs with source citations; Hybrid search & re-ranking benchmark — compare vector-only search against a BM25 plus re-ranking pipeline; Support-ticket triage automation — auto-classify tickets, retrieve relevant content, and draft replies for human review; Low-hallucination compliance RAG — a citation-strict retrieval system with an explicit 'I don't know' fallback; RAG evaluation harness — a repeatable test suite scoring faithfulness and relevance across model changes.
Is placement support included with RAG AI & Automation?
Yes — every enrolled student gets full access to our placement support: resume building, a shareable project portfolio, mock interview preparation, and guidance applying what you've built to real job applications. This is support and access, not a guaranteed job outcome — how quickly it leads to an offer depends on the market and your own effort.
