Advanced GenAI, RAG & Agentic AI
Build advanced RAG and agentic AI systems in a live 30-hour program. Explore retrieval optimization, Graph RAG, MCP, evaluation, observability and deployment through 15 structured sessions and a capstone.
Launching soon. Dates and timing confirmed before enrolment. $500 USD. 30 live hours, 15 two-hour sessions, 15 builds, 1 capstone.
Curriculum
Advanced RAG Architecture
2 hours. Explore the main components of an advanced retrieval-augmented generation architecture and how they work together.
Practical focus: Connect retrieval and generation components in an advanced RAG build.
Query Transformation and Reranking
2 hours. Understand how query transformation and reranking can improve the relevance of retrieved information.
Practical focus: Compare retrieval relevance before and after query transformation and reranking.
Agentic RAG
2 hours. Explore agent-guided retrieval and the relationship between retrieval, reasoning and tool use.
Practical focus: Work through an agent-guided retrieval flow.
Graph RAG
2 hours. Understand graph-based knowledge relationships and how they can support information retrieval.
Practical focus: Explore relationship-aware retrieval in a graph RAG build.
Multimodal RAG
2 hours. Explore retrieval across supported content modalities beyond ordinary text, within the program’s implementation scope.
Practical focus: Work with supported content modalities in a retrieval workflow.
Ingestion and Chunking
2 hours. Understand document ingestion, chunking and preparation of source material for retrieval.
Practical focus: Prepare source documents and compare chunking approaches.
RAG Evaluation
2 hours. Learn how to evaluate retrieval and generated answers using appropriate test cases and quality criteria.
Practical focus: Apply test cases to examine retrieval and answer quality.
Tracing and Observability
2 hours. Understand how execution tracing and observability help diagnose application behavior and failures.
Practical focus: Inspect a workflow trace to investigate application behavior.
LLM Routing and Cost
2 hours. Explore model-routing decisions, usage costs and trade-offs between performance, latency and expenditure.
Practical focus: Compare routing choices and their usage-cost implications.
Guardrails and Security
2 hours. Examine input validation, access restrictions and secure execution practices covered in the course.
Practical focus: Apply safeguards to an AI application workflow.
Advanced MCP
2 hours. Explore Model Context Protocol integration for connecting AI applications with compatible tools and external capabilities.
Practical focus: Connect compatible tools through an MCP integration.
Multi-Agent Orchestration
2 hours. Understand coordination across multiple agents and the management of multi-step workflows.
Practical focus: Coordinate agent responsibilities in a multi-step build.
Agent Memory and Workflows
2 hours. Explore memory and workflow state within agentic applications, within the scope of the course.
Practical focus: Examine how memory and state support an agent workflow.
Production Deployment
2 hours. Study the deployment process, configuration and operational considerations covered by the program.
Practical focus: Work through deployment configuration and operational readiness.
Capstone Project
2 hours. Integrate relevant course concepts into a production-style agentic RAG application and demonstrate the resulting solution.
Practical focus: Bring course components together and demonstrate your capstone.
Prerequisites
Working Python, basic RAG pipelines, basic agent concepts and comfort calling an LLM API.
Live slots
6:30–8:30 AM IST or 9:30–11:30 PM IST. Final timing confirmed at enrolment. Fee non-refundable once enrolment is confirmed; slot selection final.
Frequently asked questions
Who is this cohort designed for?
Software and AI engineers, ML practitioners, engineers working with LLM applications and RAG, and technical leads progressing towards advanced AI system design.
What prerequisites are required?
Working Python knowledge, experience with a basic RAG pipeline, familiarity with basic agent concepts and comfort calling an LLM API. This is an advanced technical cohort, not an introductory programming course.
What is the program duration?
30 live hours across 15 instructor-led sessions of two hours each.
What topics are covered?
Advanced RAG, query transformation and reranking, agentic, graph and multimodal RAG, ingestion, evaluation, tracing, LLM routing and cost, guardrails, MCP, multi-agent orchestration, memory, deployment and a capstone.
What will learners build?
15 hands-on builds across the published curriculum, culminating in one production-style agentic RAG capstone. Outcomes reflect work within the program, not a guarantee of a production-certified enterprise system.
What are the cohort dates and available time slots?
Launching soon. Contact MCI for the next cohort date. Proposed options are 6:30–8:30 AM IST or 9:30–11:30 PM IST. Dates, availability and local-time conversions must be confirmed before enrolment.
Can professionals join from outside India?
Yes. Professionals worldwide can enquire. MCI will confirm the corresponding local time and calendar date after the cohort schedule is finalized, accounting for daylight saving where applicable.
What is the fee?
The cohort fee is $500 USD for the published 30-hour program. Confirm applicable inclusions and any external API or hosting costs with MCI before enrolment.
What are the enrolment and refund terms?
Contact MCI, confirm dates, slot, inclusions and terms, then complete enrolment and payment following MCI’s instructions. The fee is non-refundable once enrolment is confirmed; slot selection is final.
Does an enquiry guarantee a seat?
No. An enquiry is not confirmed enrolment. MCI must confirm availability and next steps.
How can I contact MCI?
WhatsApp +91 9977220325 or email sales@mciskills.com to discuss availability and enrolment.
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