Metamorph Academy — Best Agentic AI Course in Chandigarh Call +91 95014 89999
Agentic AI · LLM · RAG · Automation · Chandigarh

Build autonomous AI agents & enterprise AI.

One of India's most advanced Agentic AI courses — design AI agents, RAG applications, multi-agent systems and LLM automation with LangChain, LangGraph, MCP and vector databases, across 16 modules, 200+ hours and production-ready projects.

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16Modules
200+Hours
RAG + AgentsProduction
4.9★Rating
Agentic AI course training in Chandigarh — LangChain, RAG and multi-agent systems
AGENTIC AI · LLMs · RAG · MULTI-AGENT · LANGCHAIN · LANGGRAPH · MCP · VECTOR DATABASES · AI AUTOMATION · PROMPT ENGINEERING · MLOPS · AGENTIC AI · LLMs · RAG · MULTI-AGENT · LANGCHAIN · LANGGRAPH · MCP · VECTOR DATABASES · AI AUTOMATION · PROMPT ENGINEERING · MLOPS ·
Agentic AI is intelligent software that plans, reasons, uses tools, retrieves knowledge and completes multi-step tasks autonomously — not just answering prompts. Metamorph Academy's Agentic AI course in Chandigarh teaches you to build these AI agents, RAG apps and multi-agent systems across 16 hands-on modules.
What Is It

What is Agentic AI — and why does it matter in 2026?

Modern businesses are moving beyond rule-based automation to intelligent agents that act on goals. Instead of scripted software, AI agents plan and execute.

▹Plan tasks independently toward a goal
▹Understand business objectives in natural language
▹Search and retrieve from enterprise knowledge bases
▹Use APIs and external tools via structured calls
▹Execute multi-step workflows end-to-end
▹Collaborate with other AI agents (multi-agent)
▹Automate customer, HR, sales and ops processes
▹Assist software development and research
✦ Expert Takeaway

Agentic AI is the shift from AI that answers to AI that acts — systems that plan, use tools, retrieve knowledge and complete multi-step tasks autonomously. The Metamorph Academy Agentic AI course in Chandigarh teaches this end-to-end across 16 modules and 200+ hours.

The Curriculum

What will you learn? — 16 modules, 200+ hours

A project-first path from AI foundations to autonomous agents and cloud deployment — every module ships a working artifact.

01

Artificial Intelligence Foundations

Artificial IntelligenceMachine LearningDeep LearningNeural NetworksGenerative AILarge Language ModelsAI EcosystemAI Engineering Fundamentals
02

Python Programming for AI

Python FundamentalsObject-Oriented ProgrammingAPIsFile HandlingVirtual EnvironmentsPackage ManagementAutomation Scripts
03

Data Processing

NumPyPandasData CleaningData TransformationFeature EngineeringData PipelinesVisualization
04

Machine Learning

Supervised LearningUnsupervised LearningRegressionClassificationClusteringModel EvaluationScikit-learn
05

Large Language Models (LLMs)

Transformer ArchitectureTokenizationContext WindowsEmbeddingsVector DatabasesPrompt OptimizationLLM Evaluation
06

Prompt Engineering

System PromptsFew-Shot PromptingChain of ThoughtStructured OutputsTool CallingFunction CallingAI Personas
07

Retrieval-Augmented Generation (RAG)

Document ProcessingEmbeddingsVector SearchKnowledge RetrievalSemantic SearchHybrid SearchEnterprise Knowledge BasesRAG Evaluation
08

Agentic AI Systems

Autonomous AI AgentsPlanning AgentsTask AgentsMemory SystemsReflection LoopsTool-Using AgentsGoal-Oriented AgentsSelf-Improving Workflows
09

Multi-Agent Systems

Multi-Agent ArchitecturesAgent CommunicationTask DelegationAgent CoordinationWorkflow OrchestrationTeam-Based AI Systems
10

AI Automation

Customer Support AutomationHR AutomationSales AutomationCRM WorkflowsLead QualificationEmail AutomationReport GenerationBusiness Process Automation
11

API Integration

REST APIsJSONAuthenticationAPI IntegrationsDatabase ConnectivityCloud APIsThird-Party Services
12

MCP & AI Tool Integration

Model Context Protocol (MCP)AI Tool IntegrationStructured Tool CallsExternal Knowledge SourcesWorkflow CoordinationSecure AI Operations
13

AI Search & Knowledge Systems

Semantic SearchEnterprise SearchAI Search OptimizationKnowledge GraphsVector DatabasesIntelligent Retrieval
14

AI Evaluation & Safety

Hallucination DetectionAI TestingEvaluation FrameworksGuardrailsResponsible AIAI SecurityPrompt Injection Protection
15

Cloud Deployment & MLOps

DockerCloud DeploymentAPI HostingCI/CDModel ServingMonitoringProduction Infrastructure
16

Capstone Project

AI Business AssistantCustomer Support AgentHR AssistantAI Sales AgentLegal Document AssistantAI Coding AssistantAI Research AssistantEnterprise Workflow Automation
✦ Expert Takeaway

A complete Agentic AI curriculum spans AI foundations, Python, LLMs, prompt engineering, RAG, single- and multi-agent systems, automation, API and MCP integration, evaluation, safety and cloud deployment — culminating in a production-ready capstone.

The Stack

Which technologies & AI tools will you master?

The exact production Agentic AI stack used by AI engineering teams in 2026.

PythonSQLGitGitHubLangChainLangGraphLlamaIndexHugging FaceOpenAI APIsChromaDBFAISSPineconeChatGPTGeminiClaudePerplexityFastAPIStreamlitDockern8nMake
✦ Expert Takeaway

The core Agentic AI stack in 2026 is Python plus LangChain, LangGraph and LlamaIndex for orchestration, vector databases (ChromaDB, FAISS, Pinecone) for retrieval, OpenAI/Claude/Gemini APIs for reasoning, and FastAPI plus Docker for deployment.

Who It's For

Who should join the Agentic AI course?

Basic programming helps but isn't mandatory — foundational support is built in for beginners.

Engineering StudentsComputer Science StudentsSoftware DevelopersData ScientistsAI EngineersIT ProfessionalsAutomation EngineersBusiness AnalystsProduct ManagersStartup FoundersEntrepreneursCareer Switchers
Careers

What jobs can you get after learning Agentic AI?

Agentic AI is one of the fastest-growing areas in AI engineering and enterprise automation.

Agentic AI EngineerAI Application DeveloperLLM EngineerPrompt EngineerAI Automation EngineerAI Solutions ArchitectRAG EngineerMachine Learning EngineerAI Product EngineerAI ConsultantEnterprise AI DeveloperAI Research EngineerAI Integration SpecialistAI Workflow Designer
✦ Expert Takeaway

Agentic AI skills map to high-paying roles — Agentic AI Engineer, LLM Engineer, RAG Engineer and AI Automation Engineer — with salaries ranging from ₹5 LPA for entry AI developers to ₹35 LPA+ for senior AI engineers in India.

Earning Potential

How much do Agentic AI engineers earn in India?

Career growth depends on technical skills, portfolio quality and project experience.

Role / ExperienceAverage Annual Salary
AI Developer₹5 LPA – ₹10 LPA
Machine Learning Engineer₹6 LPA – ₹12 LPA
LLM Engineer₹8 LPA – ₹18 LPA
AI Automation Engineer₹8 LPA – ₹20 LPA
Senior AI Engineer₹15 LPA – ₹35 LPA+
AI Consultant / EntrepreneurVaries by projects & clients

Indicative ranges based on the Indian AI job market. Actual figures vary by skills, portfolio, city and employer.

Admissions Open · Classroom + Live Online

Book a free Agentic AI demo class

Send your details on WhatsApp and our team will share the 16-module syllabus, tech stack, fees, batch timings and placement roadmap — or call us right now.

Or call / WhatsApp directly: +91 95014 89999 · Mon–Sat, 9:30 AM – 7:00 PM

Explore Programs (Inner Links)

Related courses at Metamorph Academy

The AI Stack (Outer Links)

Official technology references

Answers

Agentic AI course in Chandigarh — FAQs

Metamorph Academy offers one of the best Agentic AI courses in Chandigarh — a 200+ hour, project-first program covering AI agents, RAG, multi-agent systems, LLM automation, MCP and cloud deployment using LangChain, LangGraph and vector databases, with live enterprise projects and placement support.
Agentic AI refers to intelligent AI systems that can plan, reason, use tools, retrieve information and complete multi-step tasks autonomously, rather than simply responding to a single prompt.
Students, graduates, software developers, IT professionals, engineers, data scientists, business professionals and career changers interested in AI and automation can enrol. Basic programming helps but is not mandatory.
Basic programming knowledge is helpful, but the course includes Python fundamentals and guided practical sessions to help beginners build confidence before advanced topics.
Yes. Students build practical projects — AI assistants, RAG knowledge systems, workflow automation, customer support agents and multi-agent applications — suitable for a professional portfolio.
The curriculum includes Python, LangChain, LangGraph, LlamaIndex, Hugging Face, OpenAI APIs, vector databases (ChromaDB, FAISS, Pinecone), FastAPI, Docker, Git, n8n, Make, and platforms like ChatGPT, Gemini, Claude and Perplexity.
RAG combines large language models with an organisation's own documents and knowledge sources, letting AI systems answer using current, domain-specific information instead of relying only on pre-trained knowledge.
MCP is an open standard that lets AI models connect securely to external tools, data sources and services through structured tool calls — a core skill for building production Agentic AI systems.
Yes. Students receive career guidance, resume preparation, portfolio development, mock interviews, internship opportunities and placement assistance.
AI developers typically earn ₹5–10 LPA, LLM and AI automation engineers ₹8–20 LPA, and senior AI engineers ₹15–35 LPA+, with consultants and founders earning by projects and products. To enrol, call or WhatsApp 95014 89999.

Become an Agentic AI engineer

Book a free demo, see agents and RAG systems built live, and get a personalised roadmap into AI engineering.

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