Overview

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you will gain a solid foundation in prompt engineering, learning how to work with large language models (LLMs) effectively. You'll explore the power of prompt engineering and how to build AI-powered tools by interacting with APIs such as OpenAI and Anthropic. Through real-world examples and hands-on projects, this course will help you master the art of developing prompts that maximize the capabilities of AI models. As you move through the course, you will be guided step by step through key concepts, including setting up development environments, making your first API calls, and managing API costs. You will also delve into advanced techniques for controlling output, managing authentication, and optimizing large language models for real-time applications. Each section is designed to build your skills progressively, ensuring that you gain the practical experience needed to excel. The course culminates in a project where you will apply what you’ve learned by creating your own AI-powered tools using the skills and knowledge gained throughout the course. By the end of the course, you will have built the foundation for an AI toolbox and will have the expertise to use prompt engineering in your own projects. This course is ideal for anyone interested in learning prompt engineering, whether you're an aspiring AI developer, a data scientist, or someone who wants to gain hands-on experience in using APIs for AI-driven applications. It requires a basic understanding of programming but is accessible to beginners with a technical background. By the end of the course, you will be able to set up your development environment, make API calls, use the OpenAI Python library, build command-line interfaces, and create AI-powered tools using best practices.

Syllabus

Getting Started with Prompt Engineering

In this module, we will introduce you to the course and its objectives, exploring the significance of prompt engineering skills in AI projects. You'll get a glimpse of the course structure and key projects, with insights into how these will enhance your ability to work with LLMs. We will also set expectations for the practical application of the concepts you'll learn.

Setting Up Your Development Environment

In this module, we will guide you through setting up your development environment, ensuring you're ready to work with prompt engineering tools and APIs. You'll configure your local Python environment, set up OpenAI and Anthropic accounts, and generate API keys to start making API calls to LLMs.

OpenAI Python Library Crash Course

In this module, we will provide a hands-on crash course in using the OpenAI Python library, which will serve as the foundation for interacting with language models. You'll learn how to securely manage API keys, make your first API calls, and process API responses. Additionally, we'll cover simplifying API interactions with LiteLLM and managing model parameters to control outputs.

Project Module #1: Building the AI Toolbox Foundation

In this module, we will lay the groundwork for your first AI-powered project. You'll learn how to set up the project directory, implement the basic structure, and create a simple AI-powered "Hello World" feature. We'll also guide you through writing initial unit tests to ensure functionality and robustness.