Gen AI & Agentic AIโ€‹

4.5
Medium
12 Weeks

Gen AI & Agentic AIโ€‹

Generative AI and Agentic AI are revolutionizing the way businesses operate. While Generative AI enables machines to create content, code, images, reports, and insights, Agentic AI takes automation to the next level by creating intelligent agents that can reason, plan, make decisions, and execute tasks autonomously.

This comprehensive training program is designed for students, working professionals, developers, business analysts, and entrepreneurs who want to master the latest AI technologies and build real-world AI applications.

The curriculum combines:

  • Generative AI Fundamentals
  • Large Language Models (LLMs)
  • Prompt Engineering
  • AI Agents
  • Multi-Agent Systems
  • AI Automation
  • Retrieval-Augmented Generation (RAG)
  • AI Application Development
  • Industry Projects

Who Can Join This Course?โ€‹

  • Students
  • Freshers
  • Software Developers
  • Data Analysts
  • Business Analysts
  • Automation Professionals
  • Entrepreneurs
  • Working Professionals

Basic computer knowledge is sufficient. Python knowledge is beneficial but can be learned alongside the course.

Training Methodology

Career Opportunities After Course

Course Completion Certificate

Certification

  • AI Engineer Professional Certificate
  • Generative AI & Agentic AI Certificate
  • Capstone Project Certificate

Course Curriculum

AI Fundamentals

  • Evolution of Artificial Intelligence
  • AI vs Machine Learning vs Deep Learning
  • Generative AI Overview
  • Agentic AI Overview
  • Real-World Applications

AI Industry Landscape

  • AI Adoption Across Industries
  • Future of AI Careers
  • AI Business Transformation

Practical Session

  • AI Tool Ecosystem Overview
  • Industry Case Studies

Outcome

Understand the foundation of modern AI technologies and their business impact.

Introduction to Generative AI

  • What is Generative AI?
  • Types of Generative Models
  • AI Content Generation

Generative AI Applications

  • Text Generation
  • Image Generation
  • Audio Generation
  • Video Generation
  • Code Generation

Generative AI Use Cases

  • Marketing Content
  • Business Reporting
  • Customer Support
  • Research Assistance

Practical Labs

  • Content Generation Exercises
  • AI Productivity Workflows

Outcome

Gain a strong understanding of Generative AI capabilities and use cases.

LLM Fundamentals

  • What are Large Language Models?
  • Transformer Architecture
  • Tokens and Context Windows
  • Training vs Inference

Popular LLMs

  • GPT Models
  • Claude
  • Gemini
  • Open-Source Models

LLM Capabilities

  • Question Answering
  • Summarization
  • Translation
  • Reasoning
  • Code Generation

LLM Limitations

  • Hallucinations
  • Context Limitations
  • Bias and Safety Challenges

Outcome

Understand how modern LLMs work and how to use them effectively.

Prompt Design Fundamentals

  • Anatomy of a Prompt
  • Instruction-Based Prompting
  • Context Management

Advanced Prompting Techniques

  • Zero-Shot Prompting
  • One-Shot Prompting
  • Few-Shot Prompting
  • Chain-of-Thought Prompting
  • Tree-of-Thought Prompting

Role-Based Prompting

  • AI as Analyst
  • AI as Developer
  • AI as Consultant
  • AI as Researcher

Prompt Optimization

  • Prompt Testing
  • Prompt Refinement
  • Prompt Templates

Practical Labs

  • Business Prompt Library
  • AI Workflow Prompts

Outcome

Create professional prompts for business and technical use cases.

AI for Business

  • Market Research
  • Customer Insights
  • Business Analytics

AI for Productivity

  • Email Automation
  • Meeting Summaries
  • Documentation

AI for Development

  • Code Generation
  • Code Review
  • Debugging Assistance

AI for Content Creation

  • Blogs
  • Social Media Posts
  • Presentations

Outcome

Apply AI tools to improve productivity and business operations.

RAG Fundamentals

  • What is RAG?
  • Why RAG Matters

Components of RAG

  • Knowledge Bases
  • Embeddings
  • Vector Databases
  • Retrieval Systems

RAG Workflow

  • Data Ingestion
  • Document Processing
  • Search and Retrieval
  • Response Generation

Practical Projects

  • Document Q&A System
  • Company Knowledge Assistant

Outcome

Build AI systems that use organizational knowledge effectively.

Introduction to AI Agents

  • What are AI Agents?
  • Agent Architecture
  • Agent Lifecycle

Agent Components

  • Goals
  • Memory
  • Planning
  • Reasoning
  • Actions

Types of Agents

  • Reactive Agents
  • Goal-Based Agents
  • Autonomous Agents

Practical Examples

  • Research Agent
  • Customer Support Agent
  • Data Analysis Agent

Outcome

Understand how intelligent AI agents operate.

Agentic AI Concepts

  • Autonomous Decision Making
  • Task Planning
  • Multi-Step Reasoning

Agent Workflows

  • Goal Decomposition
  • Planning Strategies
  • Tool Selection

Agent Memory

  • Short-Term Memory
  • Long-Term Memory
  • Context Retention

Agent Communication

  • Agent Collaboration
  • Task Coordination

Outcome

Learn how Agentic AI systems perform complex tasks independently.

Tool Integration

  • Connecting AI to APIs
  • Database Access
  • Search Tools

Function Calling

  • Tool Invocation
  • Structured Outputs
  • Action Execution

Business Integrations

  • CRM Integration
  • ERP Integration
  • Analytics Systems

Practical Labs

  • AI Agent with API Access
  • Automated Business Assistant

Outcome

Enable AI agents to interact with external systems and tools.

Multi-Agent Architecture

  • Agent Collaboration Models
  • Team-Based AI Systems

Specialized Agents

  • Research Agent
  • Planning Agent
  • Execution Agent
  • Review Agent

Workflow Orchestration

  • Task Distribution
  • Agent Coordination

Real-World Applications

  • AI Project Teams
  • Business Process Automation

Outcome

Design collaborative AI agent ecosystems.

AI Automation Concepts

  • Workflow Automation
  • Intelligent Process Automation

AI Workflows

  • Lead Qualification
  • Customer Service Automation
  • Document Processing

Automation Platforms

  • No-Code Automation Tools
  • Low-Code AI Platforms

Outcome

Build end-to-end AI-powered business workflows.

AI Ethics

  • Responsible AI Principles
  • Transparency

AI Security

  • Prompt Injection Risks
  • Data Privacy

Governance Frameworks

  • AI Policies
  • Compliance Considerations

Outcome

Implement AI solutions responsibly and securely.

ย 

Application Development

  • AI Chatbots
  • AI Assistants
  • Knowledge Bots

Front-End Integration

  • User Interfaces
  • Conversational Interfaces

Deployment Concepts

  • Cloud Deployment
  • Application Monitoring

Outcome

Develop production-ready AI applications.

Application Development

  • AI Chatbots
  • AI Assistants
  • Knowledge Bots

Front-End Integration

  • User Interfaces
  • Conversational Interfaces

Deployment Concepts

  • Cloud Deployment
  • Application Monitoring

Outcome

Develop production-ready AI applications.

๐Ÿค– Enterprise AI Assistant

Build an AI assistant for employee support and knowledge management.

๐Ÿ“š AI Knowledge Management System

Create a RAG-powered document search platform.

๐Ÿ›’ AI Sales & Marketing Agent

Automate lead generation and customer engagement.

๐Ÿ“Š AI Business Analyst Agent

Generate reports and business insights from data.

๐ŸŽง Customer Support Agent

Develop an autonomous support assistant.

๐Ÿข Multi-Agent Business Workflow System

Create a team of collaborating AI agents for enterprise operations.

๐Ÿ“‘ Contract & Document Review Agent

Analyze and summarize business documents.