Agentic AI refers to artificial intelligence systems capable of autonomous decision-making and actions.

Who can enroll in the Agentic AI Training Program?

Anyone with a background in computer science, AI, or related fields can join, including students and professionals.

Do I need prior AI knowledge to join?

Basic understanding of AI or programming is recommended, but introductory modules are provided.

What topics are covered in the course?

Topics include autonomous agents, decision-making models, prompt engineering, reinforcement learning, and real-world applications.

Is this course available online?

Yes, the Agentic AI Training Program is available in both online and classroom formats.

How long is the training program?

The course duration typically ranges from 6 to 8 weeks depending on the learning pace.

Will I work on projects during the course?

Yes, the course includes hands-on projects to apply concepts and build practical skills.

Do I get a certificate after completion?

Yes, a certification is awarded upon successful completion of the program.

What career opportunities does this open up?

Graduates can pursue roles such as AI Engineer, Automation Specialist, and Intelligent Systems Developer.

Does the program offer placement assistance?

Yes, Croma Campus provides placement support and career guidance after course completion.

Home /Generative & Agentic AI/ Agentic AI Training Program

Master intelligent automation with the Agentic AI Training Program and boost your AI career potential.

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Course Duration

70 Hrs.

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3 Project

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Agentic AI Training Program

Agentic AI Introduction

AI Agents vs. Agentic AI

Comparison: Agentic AI, Generative AI, and Traditional AI

Agentic AI Building Blocks

Autonomous Agents

Human in the Loops Systems

Single and Multi Agent AI Systems

Agentic AI Frameworks Overview

Ethical and Responsible AI

Agentic AI Best Practices

AI Implementation Success Stories: Case Studies

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Agentic AI Architecture

Agentic Architecture Types

Key Components of the Agentic AI Framework

Perception Module

Cognitive Module

Action Module

Learning Module

Collaboration Module

Security Module

Agentic AI Design Patterns

Reflection Pattern

Tool Use Pattern

Planning Pattern

ReAct (Reasoning and Acting) and ReWOO (Reasoning with Open Ontology)

Multi Agent Pattern

Design Considerations

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Components and Modules

Data Ingestion and Document Loaders

Text Splitting

Embeddings

Integration with Vector Databases

Introduction to Langchain Expression Language (LCEL)

Runnables

Chains

Building and Deploying with LCEL

Deployment with Langserve

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Introduction to LangGraph

State and Memory

State Schema

State Reducer

Multiple Schemas

Trim and Filter Messages

Memory and External Memory

UX and Human-in-the-Loop (HITL)

Building Agent with LangGraph

Long Term Memory

Short vs. Long Term Memory

Memory Schema

Deployment

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What is Agentic RAG

Agentic RAG vs. Traditional RAG

Agentic RAG Architecture and Components

Understanding Adaptive RAG

Variants of Agentic RAG

Applications of Agentic RAG

Agentic RAG with Llamaindex

Agentic RAG with Cohere

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Agents

Models

Tools

Knowledge

Chunking

Vector DB

Storage

Embeddings

Workflows

Developing Agents with Phidata

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Multi Agent Systems

Multi Agent Workflows

Collaborative Multi Agents

Multi Agent Designs

Multi Agent Workflow with LangGraph

CrewAI Introduction

CrewAI Components

Setting up CrewAI environment

Building Agents with CrewAI

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Autogen Introduction

Salient Features

Roles and Conversations

Chat Terminations

Human-in-the-Loop

Code Executor

Tool Use

Conversation Patterns

Developing Autogen-powered Agents

Deployment and Monitoring

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Langfuse Overview

Langfuse Dashboard

Tracing

Evaluation

Managing Prompts

Experimentation

AI Observability with Langsmith

Setting up Langsmith

Managing Workflows with Langsmith

AgentOps Practical Implementation

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Introduction to No-Code/Low-Code AI

Benefits and Challenges of No-Code AI Development

Key Components of No-Code AI Platforms

Building AI Workflows Without Coding

Designing AI Agents with Drag-and-Drop Interfaces

Integrating No-Code AI with Existing Systems

Customizing and Fine-Tuning AI Solutions

Optimizing Performance and Efficiency in No-Code AI

Security and Compliance Considerations in No-Code AI

Best Practices for Deploying No-Code AI Solutions

Real-World Use Cases and Applications of No-Code AI

Scaling and Future Trends in No-Code AI

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Course Design By

Nasscom & Wipro

Course Offered By

Croma Campus

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Stories

success

inspiration

Abhishek

career upgrad

Upasana Singh

career upgrad

Shashank

career upgrad

Abhishek Rawat

career upgrad

Course Duration

70 Hrs.

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Weekday1 Hr/Day

Weekend2 Hr/Day

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26-Jul-2025*
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28-Jul-2025*
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23-Jul-2025*
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MON - FRI
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26-Jul-2025*
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Mor | Aft | Eve - Slot

28-Jul-2025*
Weekday

MON - FRI

Mor | Aft | Eve - Slot

23-Jul-2025*
Weekday

MON - FRI

Mor | Aft | Eve - Slot

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SELF ASSESSMENT

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