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Building an AI agent - Lab course

In this lab course, you will use python to learn to design and develop intelligent single and multi-agent systems.
Difficulty: Intermediate
Duration: Up to 12 hours and 30 minutes
Students: 50
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Content overview
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Content overview

8 steps
There are 8 Hands-on Labs in this learning path
Difficulty: Intermediate. Duration: Up to 1h 30m.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 30 minutes
A Practical Introduction to Language Models
In this lab you'll learn how to automatically summarize long pieces of text using an OpenAI model.
Difficulty: Intermediate. Duration: Up to 1h 30m.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 30 minutes
Building Single Agent Systems
In this lab you'll learn how to build a simple AI agent equipped with a tool and short memory using LangGraph and OpenAI's GPT-4o-mini.
Difficulty: Intermediate. Duration: Up to 1h 30m.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 30 minutes
Working with Multiple Agents
In this lab, you'll learn how to build a simple multi-agent system using LangGraph’s Swarm library.
Difficulty: Intermediate. Duration: Up to 1h 30m.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 30 minutes
Equipping Agents with Tools
In this lab, you will learn how to build a minimal LangGraph swarm system with agents equipped with tools using LangGraph and OpenAI's GPT-4o-mini model.
Difficulty: Intermediate. Duration: Up to 1h 30m.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 30 minutes
Building AI Agents for Good: Ethics, Risk, and Responsibility
In this lab, you will build out a multi-agent system and provide it with boundaries and ethical checks using guardrails.
Difficulty: Intermediate. Duration: Up to 1h 30m.
HANDS-ON LAB
Intermediate
Duration: Up to 1 hour and 30 minutes
Improving Agentic Systems with RAG & Prompt Engineering
In this lab you'll explore how to use prompt engineering and RAG (Retrieval-Augmented Generation) to improve agentic system performance.
Difficulty: Beginner. Duration: Up to 2h.
HANDS-ON LAB
Beginner
Duration: Up to 2 hours
Tracing, Observability, Monitoring & Evaluation in Agentic Systems
Learn about monitoring, observability, and evaluation in agentic AI systems using LangSmith and Tavily.
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