Agentic AI Fundamentals with Frameworks (3-Day Training Program)

📌 What is Agentic AI?

Agentic AI refers to AI systems capable of autonomous decision-making, planning, and action execution to achieve defined goals with minimal human intervention.

These systems are powered by Large Language Models such as GPT models and built using modern frameworks like:

• LangChain
• AutoGPT
• CrewAI
• Microsoft Semantic Kernel
• Haystack

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🎯 Course Objectives

By the end of this training, participants will:

• Understand Agentic AI concepts and architectures
• Learn how AI agents plan, reason, and act autonomously
• Build AI agents using leading frameworks
• Design multi-agent systems and workflows
• Integrate tools, APIs, and memory into agents
• Deploy and evaluate agent-based solutions
• Address ethical, security, and governance concerns

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👨‍💻 Target Audience

• AI/ML Engineers & Developers
• Data Scientists
• Product Managers & Innovation Leaders
• IT Professionals & Students
• Business Leaders exploring AI automation

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📅 Day 1: Foundations of Agentic AI & Core Architectures

🔹 Session 1: Evolution to Agentic AI

• AI → Generative AI → Agentic AI
• Differences between chatbots, copilots, and agents
• Key traits: autonomy, reasoning, goal orientation

🔹 Session 2: Anatomy of AI Agents

• Perception (input processing)
• Planning & reasoning
• Action execution
• Feedback and learning loops

🔹 Session 3: Agent Architectures

• Reactive agents
• Deliberative agents
• Hybrid agents
• Tool-augmented agents

🔹 Session 4: LLMs as the Brain of Agents

• Prompt engineering basics
• Context management
• Reasoning techniques

🛠️ Hands-on Lab:

• Build a simple rule-based agent
• Design an agent workflow (input → reasoning → output)
• Experiment with LLM prompts

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📅 Day 2: Agentic AI Frameworks & Development

🔹 Session 1: Introduction to Agentic Frameworks

• Overview of leading frameworks:
  • LangChain – chaining and tool integration
  • AutoGPT – autonomous goal-driven agents
  • CrewAI – multi-agent collaboration
  • Semantic Kernel – enterprise AI orchestration
  • Haystack – pipelines for LLM applications

🔹 Session 2: Building Agents with Frameworks

• Creating agents using LangChain
• Tool calling and API integration
• Task execution pipelines

🔹 Session 3: Memory & Knowledge Integration

• Short-term vs long-term memory
• Vector databases (conceptual overview)
• Context retention strategies

🔹 Session 4: Multi-Agent Systems

• Agent collaboration patterns
• Role-based agents
• Swarm intelligence concepts

🛠️ Hands-on Lab:

• Build an agent using LangChain
• Create a multi-agent workflow using CrewAI
• Integrate APIs/tools into agents

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📅 Day 3: Applications, Deployment & Governance

🔹 Session 1: Real-World Use Cases

 

• Business process automation
• AI copilots and assistants
• Autonomous research and coding agents
• Enterprise AI workflows

🔹 Session 2: Deployment & Integration

• Deploying agents in cloud environments
• API integration strategies
• Monitoring agent performance

🔹 Session 3: Risks, Ethics & Governance

• Hallucinations and reliability
• Security risks and data privacy
• Bias and fairness
• Responsible AI frameworks

🔹 Session 4: Future of Agentic AI

• Autonomous enterprises
• Human-AI collaboration
• Industry trends and opportunities

🛠️ Hands-on Lab:

• Build and deploy an AI agent use case
• Evaluate agent performance and outputs
• Implement basic governance controls

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📊 Capstone Project

• Design a real-world Agentic AI solution
• Use at least one framework (LangChain / CrewAI / Semantic Kernel)
• Integrate tools, memory, and multi-agent workflows
• Present business value and architecture

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📘 Tools & Technologies Covered

• LLMs (GPT-based models)
• LangChain, AutoGPT, CrewAI
• Microsoft Semantic Kernel
• Haystack framework
• APIs and tool integrations
• Vector databases (conceptual)
• Cloud deployment basics

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📄 Assessment & Certification

• Hands-on lab performance
• Capstone project evaluation
• Certificate of Completion

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❓ FAQs

1. What is Agentic AI?

AI systems that autonomously plan and execute tasks.

2. Which frameworks are used in Agentic AI?

LangChain, AutoGPT, CrewAI, Semantic Kernel, and Haystack.

3. Do I need coding skills?

Basic programming is helpful but not mandatory.

4. What is a multi-agent system?

Multiple AI agents collaborating to solve problems.

5. What is LangChain used for?

Building LLM-powered applications and agents.

6. What is CrewAI?

A framework for orchestrating multiple AI agents.

7. What are risks in Agentic AI?

Bias, hallucinations, and security concerns.

8. Can Agentic AI be used in business?

Yes, for automation, decision-making, and productivity.

9. What is the role of memory in AI agents?

To retain context and improve decision-making.

10. What is the future of Agentic AI?

Autonomous systems driving enterprise operations.

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📢

Master Agentic AI with frameworks in this 3-day training covering AI agents, LangChain, CrewAI, AutoGPT, Semantic Kernel, multi-agent systems, and real-world applications.

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