Prompt Engineering in Python, with GPT, and the OpenAI API

Overview

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Master the art of prompt engineering in Python and unlock the full potential of GPT models and the OpenAI API. This course will teach you how to create, improve, and fine-tune prompts for various tasks, from personal coaching to building chatbots. You'll gain hands-on experience in iterative prompt design, mitigating hallucinations, and extracting structured information with JSON mode. The course begins with an introduction to prompt engineering fundamentals and explores how GPT models work in practical scenarios. You'll learn to set up your OpenAI API key, implement chain-of-thought prompting, and compare model versions like GPT-3.5 and GPT-4. Through real-world examples, you’ll also tackle advanced topics such as emotion-driven prompts and exponential backoff strategies. In later modules, you'll build your own Python API chatbot, enhance multi-turn conversations, and use GPT for extracting numerical values and image-based input. Techniques like "prompt hacking" and smart prompting will teach you how to maximize GPT’s performance, even with older models. This course is ideal for developers, data enthusiasts, and AI professionals seeking to master prompt engineering. Basic Python knowledge is required, and the course is designed for an intermediate difficulty level.

Syllabus

Introduction

In this module, we will introduce the course by outlining its structure, goals, and unique value propositions. You will gain an understanding of prompt engineering basics and learn how the course content and instruction remain up-to-date with cutting-edge developments in the field.

ChatGPT as a Personal Coach

In this module, we will explore how to leverage ChatGPT as a personal coach to support your growth and learning. You will learn how to access course materials, craft coaching prompts, and identify the limitations of the tool. Additionally, we’ll discuss using custom GPTs to elevate your Python learning experience.

Building up Prompts, Mitigating Hallucination, and Getting the Best Answers

In this module, we will dive into advanced prompting strategies to maximize GPT's capabilities while addressing common challenges. You will learn to iteratively improve prompts, apply chain-of-thought methods, and mitigate hallucinations. Additionally, you’ll explore findings from research like EmotionPrompt and implement practical solutions for real-world scenarios.

Python API Chat Bot, and Prompt Hacking

In this module, we will focus on building a chat bot using the Python API and refining prompt engineering techniques for advanced use cases. You will learn how to enhance conversation flow through prompt hacking and implement exponential backoff strategies for robust, multi-turn interactions.

Extracting Numerical Values from Text Data, Testing your Prompts, and JSON Mode

In this module, we will focus on techniques for extracting numerical values from text data and validating the accuracy of your extraction methods. Additionally, you will explore how to leverage JSON mode and optimize prompts to push GPT-3.5 performance closer to GPT-4, unlocking more powerful and structured outcomes.

Multimodal Prompting

In this module, we will explore the concept of multimodal prompting, focusing on how GPT models interpret and utilize images. You will learn how to incorporate visual inputs into prompts to provide richer context and improve the accuracy of model outputs.