COURSE
Agent Foundations
The Agent Foundations course takes you through the core concepts behind AI agents, multi-agent systems, and agentic AI. You will learn how agents perceive, decide, and act, how multi-agent systems are structured, and how to deploy them responsibly. The knowledge you build here is the foundation for everything else in agentic AI development. Complete the course, pass the final exam, and earn your official Agent Academy certification.
Approx. 2.5 hours
5 modules
Beginner level
Self-paced
Free
Certification included
Five modules, one solid foundation
Learning Pathway
When one agent is not enough. Learn how multiple specialized agents coordinate to tackle complex, multi-step problems that a single agent could not handle alone.
What you will learn:
- Define what a multi-agent system is and how it differs from a single-agent approach
- Understand agent roles, specialization, and how responsibilities get distributed across a system
- Explain the basics of agent coordination and how agents stay aligned on a shared goal
- Recognize the scenarios where multi-agent systems create the most value
30 minutes
5 lessons
Module quiz
Agentic AI gets used loosely to mean almost anything. This module gives you a clear, working definition and shows how it actually differs from the other terms it gets confused with.
What you will learn:
- Define agentic AI and identify the five characteristics that make a system agentic rather than just responsive
- Understand the perception, planning, action, and evaluation loop that agentic systems run on
- Distinguish agentic AI from generative AI, individual agents, and multi-agent systems
- Recognize the core advantages agentic AI brings to organizations, and the key challenges to design for
35 minutes
5 lessons
Module quiz
Language models have a knowledge cutoff and no access to your private data on their own. This module covers the technique that fixes that, and how agentic RAG takes it further.
What you will learn:
- Define RAG and explain how a standard retrieval pipeline works
- Understand how RAG differs from AI agents and why that distinction matters
- Recognize where traditional RAG falls short in real-world systems
- Explain what agentic RAG is and when it's the right architectural choice
25 minutes
4 lessons
Module quiz
Working in a demo and working in production are two different problems. This module covers what has to be true for an agent system to be trusted with real data and real workflows.
What you will learn:
- Explain what responsible AI means and why it applies directly to agent systems
- Understand how to handle sensitive and personal data safely in agentic workflows
- Describe what observability means for agents and why it's essential in production
- Identify the security threats specific to agentic systems and how to test for reliability
30 minutes
5 lessons
Module quiz
This is the last step. The exam covers all five modules and tests your understanding of AI agents, multi-agent systems, agentic AI, RAG, and responsible deployment. Pass and you will receive your official Cognizant AI Lab Agent Foundations certification, which you can download, share on LinkedIn, and add directly to your profile as a verified credential.
What the exam covers:
- Demonstrate your understanding of AI agents, how they work, and where they create value
- Apply your knowledge of multi-agent systems, agentic AI, and agentic RAG concepts
- Show you understand the principles of responsible and safe agent deployment
- Earn your official Agent Foundations certification from Cognizant AI Lab
10 minutes
4 questions
Shareable certificate
Add to LinkedIn
