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Agentic AI Course

Learn how to build autonomous AI agents using LangGraph, CrewAI, AutoGen, and more. This Agentic AI course offers hands-on experience with multi-agent systems, PromptOps, and RAG pipelines—tailored for professionals looking to master AI agent development.

Explore our flexible online Agentic AI program in India, with a detailed syllabus, certification, and placement support. Check course fees, apply for a free session, or download the full syllabus today.

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What Is Agentic AI?

Agentic AI refers to autonomous AI systems that can reason, plan, use tools, and execute multi-step tasks without constant human input. Unlike traditional chatbots, AI agents leverage frameworks like LangGraph, CrewAI, and AutoGen to orchestrate complex workflows end-to-end.

What Will You Build in This Agentic AI Course?

  • Multi-agent customer-support pipeline
  • RAG-powered research & retrieval agent
  • Autonomous code-review & DevOps agent
  • Enterprise workflow automation system

Who Is This Agentic AI Course For?

  • Product managers & workflow designers
  • Software engineers & ML developers
  • Enterprise & innovation-team leads
  • Data scientists transitioning to AI agents

Agentic AI Course Overview

A comprehensive training program designed to transform developers into autonomous AI system architects, covering everything from agent fundamentals to production deployment.

12 Weeks
Duration
8+ Hands-on
Projects
Live + Recorded
Mode
Industry Recognized
Certificate
01

Autonomous Agent Development

Build self-governing AI agents capable of reasoning, planning, and executing complex tasks without constant human oversight.

02

Multi-Agent Orchestration

Design collaborative agent networks using LangGraph, CrewAI, and AutoGen for enterprise-scale workflow automation.

03

Advanced Reasoning Patterns

Master ReAct, Chain-of-Thought (CoT), and Tree-of-Thought (ToT) prompting strategies for intelligent decision-making.

04

Production-Ready Deployment

Deploy secure, scalable AI agents with MCP integration, observability tools, and enterprise-grade guardrails.

What You'll Learn

Master autonomous AI agent development with LangGraph, CrewAI, and AutoGen. Learn ReAct, CoT, and ToT reasoning patterns while building production-ready multi-agent systems.

Career Outcomes

Become an AI Agent Engineer, Automation Architect, or AI Solutions Developer. Work with cutting-edge agentic AI frameworks used by leading tech companies worldwide.

Why Choose Our Agentic AI Course?

9 reasons engineers and product leaders pick this Agentic AI course.

Build Real Autonomous Agents

Design and deploy agents with reasoning, memory, and multi-step workflows across real-world tasks.

Multi-Agent System Expertise

Coordinate teams of agents using CrewAI and LangGraph to solve complex enterprise problems.

Hands-on with LangChain & AutoGen

Master the most advanced frameworks to build, debug, and optimize agent-based applications.

Enterprise-Ready RAG & Memory

Fuse retrieval with long-term memory for smarter agent cognition using vector DBs and LangChain.

PromptOps & Agent Reasoning

Implement advanced prompting patterns—ReAct, CoT, ToT—for higher-quality agent decisions.

Secure Agent Deployment (MCP)

Deploy agents using Model Context Protocol (MCP), sandboxing, and secure function calling.

AgentOps, Tracing & Guardrails

Learn how to monitor, trace, and apply cost-control guardrails to production agent workflows.

SDKs for Real Deployment

Access OpenAI SDK, Google A2A, CrewAI, and LangGraph in real projects and GitHub-ready stacks.

Mentorship from Agentic Engineers

Learn from engineers building agent-based systems in real startups, products, and research labs.

Who Should Join This Agentic AI Program?

Choose the path that matches your role. All tracks include live sessions, projects, and certification.

Product & Workflow Track

Product / Project Managers

UI-based, workflow & no-code focus

  • Automate business workflows with Zapier, Make, and n8n
  • Evaluate and deploy no/low-code AI agents for teams
  • Understand RAG, prompt engineering, and agent capabilities
View curriculum
Engineering & Architecture Track

Engineers (Software / ML / AI / DS)

Deep architecture, production-grade agents

  • Build multi-agent systems with LangGraph, AutoGen, and CrewAI
  • Master ReAct, CoT, ToT reasoning + MCP secure deployment
  • Ship agent pipelines with AgentOps, tracing, and guardrails
View curriculum
Enterprise Cohort

Enterprise Teams

Upskilling, ROI, and governance

  • Custom cohorts for 5–50+ employees with tailored pace
  • AI governance, cost control, and compliance guardrails
  • Measurable ROI: agent-driven process gains in 12 weeks
View curriculum

Prerequisites (kept practical): Basic Python or prompt-engineering knowledge is helpful. We cover all essential concepts before advancing to multi-agent architectures.

Skills You'll Gain in This Agentic AI Program

Real engineering skills interviewers test for AI Agent & Automation roles — not just tool names.

Autonomous Agent DesignMulti-Agent OrchestrationReAct & Chain-of-Thought ReasoningTree-of-Thought PlanningAgent Memory ArchitectureContext-Window ManagementRAG Pipeline EngineeringPrompt Engineering for AgentsFunction-Calling & Tool UseSecure Agent Deployment (MCP)AgentOps & ObservabilityCost & Token OptimizationWorkflow Automation DesignError Recovery & GuardrailsAgent Testing & EvaluationMulti-Modal Agent Coordination

Industry-Ready: Every skill taught in this Agentic AI course is mapped to real-world job requirements from top AI companies and enterprise environments.

Agentic AI Tools & Frameworks You'll Master

Gain hands-on expertise with industry-leading tools powering autonomous AI systems at top technology companies worldwide.

Orchestration

LangGraph

Graph-based framework for building reactive, persistent multi-agent workflows with state management.

Workflow DesignState MachinesAgent Coordination
Collaboration

CrewAI

Role-based agent collaboration framework enabling task delegation and parallel agent execution.

Team AgentsTask DelegationRole Assignment
Multi-Agent

AutoGen

Microsoft's conversational multi-agent framework supporting multi-turn dialogue and tool usage.

ConversationsCode GenerationProblem Solving
Foundation

OpenAI SDK

Core SDK for GPT models with function calling, structured outputs, and assistant capabilities.

Function CallingAssistants APIEmbeddings
Framework

LangChain

Comprehensive framework for building LLM applications with chains, agents, and memory systems.

ChainsAgentsMemory
Observability

LangSmith

Debug, trace, and evaluate prompt chains and agent runs with visual insights and analytics.

TracingEvaluationDebugging
Security

Model Context Protocol

Secure, auditable LLM-to-tool communication via WebSocket or SSE with sandboxed execution.

Tool AccessSecurityAudit Logs
Vector DB

Qdrant & FAISS

High-performance vector databases for semantic search, embeddings storage, and RAG pipelines.

EmbeddingsSimilarity SearchRAG
8+
Enterprise Frameworks
15+
Hands-on Projects
100%
Production Ready

Agentic AI Course Roadmap

12 modules over 12 weeks — from agent fundamentals to production-grade capstone projects.

Module 1

01.Agentic AI Foundations

  • Agent types: Reactive, Goal, Utility, Learning
  • Core loop: Sense → Think → Act → Learn
  • Build your first agent using LangChain
Module 2

02.Build Agents with AutoGen

  • Roles, chats, tool routing in AutoGen
  • Tool chaining and data pipelines
  • Project: Email/report writing agent
Module 3

03.LangGraph Agent Workflows

  • Nodes, edges, retry/fallback patterns
  • Memory + condition-based routing
  • Project: Customer support bot
Module 4

04.PromptOps & Reasoning

  • CoT, ReAct, Tree of Thought, DSP
  • Prompt tuning for structured tools
  • Function-calling APIs and refinement
Module 5

05.Multimodal Architectures

  • CrewAI for text teams
  • Vision agents: CLIP, LLaVA
  • Voice agents: Whisper, XTTS
Module 6

06.Multi-Agent Collaboration

  • Role assignment and task splits
  • Chat-based vs orchestration agents
  • Lab: Transcribe → Fetch → Visualize
Module 7

07.Retrieval-Augmented Agents

  • Chunking, embedding, hybrid retrieval
  • Smart prompt merging with memory
  • Project: PDF chat + assistant agent
Module 8

08.Model Context Protocol

  • MCP client-server setup
  • Protocols: SSE, WebSocket
  • Use case: Agent-to-API bridge
Module 9

09.Agent SDKs & Frameworks

  • OpenAI Agents SDK: Tooling + Handoffs
  • Google A2A for decentralized agents
  • Compare: LangGraph vs AutoGen
Module 10

10.AgentOps & Monitoring

  • LangSmith, SuperAgent, Helicone
  • Cost tracing, error recovery
  • Guardrails, fallback strategies
Module 11

11.Agent Design Patterns

  • Centralized vs distributed flows
  • Stateless vs stateful memory patterns
  • CoT, ReAct, Event-driven agents
Module 12

12.Capstone Agent Projects

  • RAG-powered tutor agent
  • Debug assistant with memory
  • Multi-agent sales bot with vision

Agentic AI Course Curriculum & Syllabus

Choose your path: Business workflow automation or production-grade AI agent engineering. Enterprise cohorts available.

Download Brochure

What Sets Our Agentic AI Training Apart

Agentic AI Course vs free alternatives — see the difference.

Multi-Agent Architectures

✔ Learn LangGraph, AutoGen, and CrewAI to build scalable multi-agent workflows with context sharing.
✘ Focuses on prompt chaining only; lacks orchestration or system-level design.

PromptOps & Agent Reasoning

✔ Implements advanced PromptOps like CoT, ReAct, ToT, and ReWOO for step-by-step reasoning.
✘ Teaches only static prompts without agent memory or planning.

Secure Deployment (MCP)

✔ Covers MCP for secure tool calling, sandboxing, and authenticated execution flows.
✘ No security context, missing authenticated or scoped agent calls.

RAG with Memory & Retrieval Agents

✔ Build agents with long-term memory, vector search, and contextual RAG modules.
✘ Abstract overview only; lacks persistent memory or document grounding.

Live Mentorship & Project Feedback

✔ Blueprint reviews, use-case mentoring, and prompt chain debugging from experts.
✘ No live sessions or code-level guidance.

Capstone Projects & Certification

✔ Versioned agent projects with GitHub repo + shareable School of Core AI certification.
✘ Basic certs only, no project-based assessment.

Placement Support & ROI

✔ Job pipeline, mock interviews, resume revamp, and referral network—all included.
✘ No career support, alumni tracking, or hiring help.

Agentic AI Course Certification

Upon completing the Agentic AI Course, you'll receive an industry-recognized certificate from the School of Core AI—validating your expertise in autonomous agents, multi-agent systems, LangGraph, and production deployment.

CERTIFICATE

OF ACHIEVEMENT

THIS IS TO CERTIFY THAT

SCHOOL
OF
CORE
AI

RAHUL SHARMA

Date : 12th Feb 26

Has Successfully Completed The

Comprehensive Agentic AI Engineering Program

Conducted By The School Of Core AI.

This Intensive Program Included Hands-On Training In LangGraph, CrewAI, AutoGen, Multi-Agent Systems, PromptOps (ReAct, CoT, ToT), RAG Pipelines, Model Context Protocol (MCP), Agent Memory Systems, LangSmith Observability, And Production-Grade Agentic AI Deployment.

Aishwarya Pandey

Founder and CEO

Certification ID :

RAHULSHARMA120226

SCHOOL
OF
CORE
AI

This certificate validates your expertise in building production-ready autonomous AI agents with multi-agent orchestration, advanced reasoning patterns, and enterprise-grade deployment.

Agentic AI Course Fees & Enrollment

One all-inclusive fee for 12 weeks of Live ILT, guided projects, capstone demo, and a verifiable certificate.

Admissions openNext live batch: 15th–30thSmall batches

One-time payment

₹35,000

12 weeks • Live ILT • Capstone

Duration: 12 weeks
Format: Live + Recorded
Projects: 8+ hands-on + capstone
Certificate: verifiable
Enroll / Get Fee DetailsTalk to our team: +91 96914 40998

We confirm exact batch timings and schedule fit during the call.

₹35,000 includes Live ILT, guided projects, capstone, certificate, and placement support — no hidden charges.

What you'll get

  • Live instructor-led sessions with clear milestones on LangGraph, CrewAI, AutoGen.
  • 8+ portfolio-grade agent builds + 1 capstone multi-agent project.
  • Code reviews, debugging help, and agent architecture guidance.
  • Interview + portfolio support (resume review, project narration, mock rounds).
  • Lifetime recordings + updates access for revisions.

Best for working developers: plan for ~8–10 hrs/week (live sessions + build time).

Get the complete enrollment planCall: +91 96914 40998

Agentic AI Course fees are 35,000 INR for a 12 week live instructor-led training program with hands-on projects, capstone demo, and verifiable certificate.

Agentic AI Course Reviews & Testimonials

Hear how professionals transformed their careers with Agentic AI

"The Agentic AI course transformed my understanding of autonomous systems. I moved from automation to mastering LangGraph, RAG, and agent orchestration. It helped me become a certified Gen AI Engineer and build production-ready agent pipelines."
Rahul Sharma
Gen AI Engineer, EY
"I transitioned to Agentic AI through this course. It covered everything—LangGraph, AutoGen, PromptOps, and deploying agents on Kubernetes. This hands-on training made me confident in building scalable, secure AI agents."
Yusuf Jafar
Deep Learning Engineer, TCS
"Coming from analytics, I used this course to dive into agentic design—RAG, vector databases, function calling, and secure tool usage with MCP. Now I build enterprise-grade agent architectures confidently."
Nitin Gupta
AI Engineer, Enterprise AI Team
"The Agentic AI course was a deep dive into LangGraph workflows, secure deployments with MCP, and agent tracing using LangSmith. I apply these tools directly in my work on AI-driven medical systems."
Om Yadav
Machine Learning Engineer, HealthTech
"I focused on agent reasoning and multimodal coordination. From ReAct and ToT prompting to fine-tuned diffusion models and function-calling agents—the Agentic AI course was research-backed and practical."
Aihwarya Patel
AI Research Engineer, Creative AI Lab
"This course helped me level up to an Agentic AI architect. I built pipelines using LangGraph, PromptOps, and MCP-secured tool access. I now lead agent design for mission-critical GenAI features."
Rahul Raj
Gen AI Engineer, Startup CTO Office

Agentic AI Course — Frequently Asked Questions

Everything you need to know about the Agentic AI Course.

Got More Questions?

Talk to Our Team Directly

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Enquire Now +91 96914 40998 info@schoolofcoreai.com
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