Building Your First AI Agent with OpenAI

This course is part of Build Powerful AI Agents with OpenAI Tools Professional Certificate

Instructor: Professionals from the Industry

Access provided by PALC Dev

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

10 assignments¹

AI Graded see disclaimer

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your Software Development expertise

This course is part of the Build Powerful AI Agents with OpenAI Tools Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Coursera

There are 4 modules in this course

The Building Your First AI Agent with OpenAI course provides a practical introduction to creating intelligent, tool-using AI agents. Learners begin by understanding the key differences between reactive chatbots and proactive agents, mapping out the five core components of agentic architecture.

The course then explores the OpenAI Responses API, GPT-4/5 models, and built-in tools such as browser, code interpreter, and file search, showing how they extend agent capabilities for real-world tasks. Through guided lessons, learners configure secure API access, manage tokens and costs, and design system prompts that define agent behavior. They also add reasoning patterns like chain-of-thought and reflection to improve reliability, before integrating multiple tools into a unified agent system. Hands-on projects, including building a technical support agent, reinforce skills in architecture design, tool integration, and performance optimization. By the end, learners will have built a fully functioning AI agent capable of handling complex multi-step tasks and decision-making with autonomy and reliability.

As a new Associate Consultant with the AI consultancy Praxis AI, you will address the limitations of Innovate Logistics' failing customer support chatbot. Your goal is to apply the ACTOR framework to diagnose why the current system fails and design a comprehensive architectural blueprint for a new autonomous agent, utilizing the five core components of intelligent AI systems.

What's included

2 videos7 readings3 assignments

2 videos Total 12 minutes

The Five Core Components That Make an Agent 8 minutes
The OpenAI Agent Ecosystem in Action 4 minutes

7 readings Total 145 minutes

Why Your Business Needs Agents, Not Just Chatbots 20 minutes
Agent Architecture Patterns and Decision Framework 10 minutes
Hands on Activity: Design Your Agent Architecture 30 minutes
Mapping OpenAI Tools to Agent Architecture 20 minutes
Activity: Build Your OpenAI Stack Blueprint 25 minutes
Tool Design Patterns and Best Practices 15 minutes
Activity: Design Your Tool Strategy 25 minutes

3 assignments Total 120 minutes

Agents vs. Chatbots Fundamentals 30 minutes
OpenAI Agent Stack Mastery 30 minutes
Module 1 Assessment 60 minutes

Stepping into the role of Prototype Developer at Praxis AI, you will write the code that powers the Innovate Logistics agent's core existence. You will build a production-grade API client that prioritizes security, cost management, and reliability, and then construct a conversational agent capable of maintaining context and following complex behavioral instructions via system prompts.

What's included

3 videos3 readings2 assignments2 ungraded labs

3 videos Total 23 minutes

Your First Steps with the OpenAI API 8 minutes
Building a Production-Ready API Client 7 minutes
From API to Agent: Your First Intelligent System 7 minutes

3 readings Total 85 minutes

API Best Practices and Cost Optimization 45 minutes
Agent Design with System Prompts 20 minutes
Reasoning Patterns for AI Agents 20 minutes

2 assignments Total 90 minutes

API Setup and Management 30 minutes
Module 2 Assessment 60 minutes

2 ungraded labs Total 50 minutes

Build Your API Client Foundation 25 minutes
Create Your Q&A Agent Foundation 25 minutes

Acting as an Integration Specialist for Praxis AI, you will give the Innovate Logistic agent the tools it needs to solve real business problems. You will implement the Web Search tool for real-time shipping data, deploy File Search (RAG) to access internal policy documents, and utilize the Code Interpreter to build a separate internal agent that analyzes performance logs for management.

What's included

3 videos4 readings3 assignments3 ungraded labs

3 videos Total 17 minutes

Configuring and Optimizing Browser Tool Usage 8 minutes
Implementing Document Search and Retrieval 3 minutes
Adding Analytical Power to Your Agent 5 minutes

4 readings Total 95 minutes

Your Agent and How it Interacts with OpenAI Tools 10 minutes
Search Strategy Design and Information Synthesis 45 minutes
Document Processing and Retrieval Patterns 20 minutes
Code Interpreter for Data Analysis 20 minutes

3 assignments Total 120 minutes

Browser Tool Mastery 30 minutes
File Search Fundamentals 30 minutes
Module 3 Assessment 60 minutes

3 ungraded labs Total 70 minutes

Build Search-Enabled Support Agent 25 minutes
Build a Policy Documentation Assistant 25 minutes
Create Analytical Agent 20 minutes

In the role of Lead Architect at Praxis AI, you will refactor the disparate tools of the Innovate Logistics Agent into a single, unified intelligent system. You will write the decision-making logic that orchestrates tool usage, implements cost-saving caching and resilient fallback patterns, and validates the final agent through a rigorous mock-and-live testing strategy.