Course • 8 Weeks • Registrations Open 🎓 Certificate Provided 💼 Reimbursable via Corporate L&D Limited Offer: ₹9,999

Mastering Agentic AI Foundations
Path to AI Architect

Lead your path to an AI Architect in 8 weeks. Learn AI Engineering, Tool Calling, Model Context Protocol (MCP), Agentic QA, RAG workflows, and AI Evaluation pipelines.

Course Overview

Moving from simple LLM wrappers to multi-agent production architectures is where the highest value lies in AI today. This course equips engineering leads, developers, and architects with the exact system patterns needed to build, evaluate, and scale Agentic AI systems with confidence.

⚙️ Tool Calling & MCP

Master Tool Integration and Anthropic's Model Context Protocol (MCP) to connect LLMs to enterprise databases and APIs.

🔍 RAG & Context Engineering

Implement dense/sparse hybrid search, reranking, and document parsing pipelines tailored for codebases and test suites.

🤖 Agentic QA & Control Planes

Build autonomous test execution agents, AI-as-a-Judge evaluation pipelines, and security guardrails.

💬 Mid-Week Office Hours

Clear doubts, get personalized project guidance, and review code in our mid-week live office hours.

Syllabus Breakdown

8 Weeks • 2 Hrs/Week + Office Hours
Week 1

Introduction to AI Engineering & IDEs

Modern AI engineering concepts, AI IDEs, context windows, and environment setup.

Week 2

Prompt Engineering (Basic to Advanced)

Chain-of-Thought prompting, zero/few-shot techniques, system prompts, and structured outputs for testing.

Week 3

Agent Architecture, Tool Calling & MCP

Intelligent agent state machines, tool calling protocols, and Model Context Protocol (MCP) integrations.

Week 4

Designing RAG for Engineering Workflows

Advanced RAG patterns, GraphRAG, Hybrid RAG architecture tailored for internal docs, test suites, and codebase context.

Week 5

AI Agent Evaluation & AI-as-a-Judge

Evaluating non-deterministic outputs, metric scoring, and implementing AI-as-a-Judge patterns for test validation.

Week 6

AI Guardrails, Observability & Tracing

AI Guardrails (Nvidia NeMo), OWASP Top 10 for LLMs, prompt injection defense, LLM Tracing, and Arize AI observability.

Week 7

Multi-Agent Systems & Orchestration

Multi-agent architectures,orchestrator-worker, supervisor, swarm ,LangGraph, Agent-to-agent communication protocols,Discussion on capstone project

Week 8

Capstone Projects

Build and present a production-grade use case and create your portfolio.

Hosted By

RR

Rama Rajeswari

AI Practitioner and Entrepreneur. With 20+ years of industry experience and an IIT Guwahati AI certification, Rama specializes in enterprise Agentic systems, multi-agent workflows, and LLM evaluation pipelines. Spanning startups to Fortune-scale MNCs, her focus is on practical, battle-tested tool application over textbook theory.

Previous Enterprise Experience:
Chargebee Cisco Oracle Circles

Who Is This Course For?

Software Engineers

Aiming to master agentic software engineering and production AI architectures.

Technical PMs & Leads

Looking to lead AI product engineering with complete technical clarity.

Architects & QA Leads

Designing enterprise LLM platforms, context systems, and automated test guardrails.

Frequently Asked Questions

What is the weekly schedule for the live sessions?
16 total hours of live training: Standard Track (2 hrs/day on weekends over 8 weeks) or Weekday Fast-Track (2 hrs/day over 8 days), plus optional mid-week office hours for doubt resolution and code reviews.
When will cohort dates be finalized?
We collect student schedule preferences (Weekend vs Weekday) prior to finalizing exact batch start dates. Fill out the Enquiry Form to select your preference and lock in the promotional ₹9,999 pricing!
How do I enroll in my selected cohort?
Simply select your desired cohort timeline radio button in the enrollment box and click the "Claim Now" button to connect directly with our admissions team on WhatsApp.
What are the prerequisites for this course?
Basic proficiency in software engineering (Python/TypeScript) and a foundational understanding of web APIs or software architecture is recommended.