uCertify

AI Agents in Practice

(AI-AGENTS.AJ1)
Lessons
Lab
AI Tutor (Add-on)
Get A Free Trial

Skills You’ll Get

Download Course Outline

1

Introduction

  • Who this course is for
  • What this course covers
  • To get the most out of this course
2

Evolution of GenAI Workflows

  • Understanding foundation models and the rise of LLMs
  • Latest significant breakthroughs
  • Road to AI agents
  • The need for an additional layer of intelligence: introducing AI agents
  • Summary
  • References
3

The Rise of AI Agents

  • Evolution of agents from RPA to AI agents
  • Components of an AI agent
  • Different types of AI agents
  • Summary
  • References
4

The Need for an AI Orchestrator

  • Introduction to AI orchestrators
  • Core components of an AI orchestrator
  • Overview of the most popular AI orchestrators in the market
  • How to choose the right orchestrator for your AI agent
  • Summary
  • References
5

The Need for Memory and Context Management

  • Different types of memory
  • Managing context windows
  • Storing, retrieving, and refreshing memory
  • Popular tools to manage memory
  • Summary
  • References
6

The Need for Tools and External Integrations

  • The anatomy of an AI agent’s tools
  • Hardcoded and semantic functions
  • APIs and web services
  • Databases and knowledge bases
  • Synchronous versus asynchronous calls
  • Summary
  • References
7

Building Your First AI Agent with LangChain

  • Introduction to the LangChain ecosystem
  • Overview of out-of-the-box components
  • Use case – e-commerce AI agent
  • Summary
  • References
8

Multi-Agent Applications

  • Introduction to multi-agent systems
  • Understanding and designing different workflows for your multi-agent system
  • Overview of multi-agent orchestrators
  • Building your first multi-agent application with LangGraph
  • Summary
  • References
9

Orchestrating Intelligence: Blueprint for Next-Gen Agent Protocols

  • What is a protocol?
  • Understanding the Model Context Protocol
  • Agent2Agent
  • Agent Commerce Protocol
  • Toward an agentic web
  • Summary
  • References
10

Navigating Ethical Challenges in Real-World AI

  • Ethical challenges in AI – fairness, transparency, privacy, and accountability
  • Agentic AI autonomy and its unique ethical challenges
  • Guardrails for safe and ethical AI
  • Content filtering and moderation in AI systems
  • Addressing the challenges: governance, regulations, and collaboration
  • Summary
  • References

1

Evolution of GenAI Workflows

2

The Rise of AI Agents

3

The Need for an AI Orchestrator

4

The Need for Memory and Context Management

5

The Need for Tools and External Integrations

  • Understanding Tools in AI Agents
6

Building Your First AI Agent with LangChain

7

Multi-Agent Applications

8

Orchestrating Intelligence: Blueprint for Next-Gen Agent Protocols

  • Understanding AI Protocols and the Agentic Web
9

Navigating Ethical Challenges in Real-World AI

  • Understanding Ethical Challenges in AI and Agentic Systems

Any questions?
Check out the FAQs

Still have unanswered questions and need to get in touch?

Contact Us Now

Related Courses

All Courses
We use cookies for improving site experience and analytics. Learn More