The Complete Prompt Engineering For Ai Bootcamp (2023)

Learn practical skills for working with AI professionally, including ChatGPT, Midjourney, and GitHub Copilot.

What you'll learn

Recall the most commonly used AI tools and their relative strengths or weaknesses

Recognize the core tenets of prompt engineering, as well as common tips & tricks

Apply what you’ve learned to generate a new AI products in 5 real-world projects

Understand the concepts and tooling you need to run AI reliably in production

Requirements

Basic Python Skills

Description

Are you eager to dive into the world of AI and master the art of Prompt Engineering? The Complete Prompt Engineering for AI Bootcamp (2023) is your one-stop solution to learn all about working with cutting-edge AI tools like ChatGPT, Midjourney, GitHub Copilot, GPT-4, DALL-E, and Stable Diffusion!Whether you're an aspiring AI engineer or a seasoned professional looking to upgrade your skills, this comprehensive bootcamp has got you covered. You'll learn practical techniques to harness the power of AI for various professional applications, from generating text and images to enhancing software development and boosting your creative projects.The number of papers published on AI every month is growing exponentially, and it’s becoming increasingly difficult to keep up. The open-source project Stable Diffusion is the fastest growing repository in GitHub in history, and ChatGPT is the fastest growing consumer product in history, hitting 1 million users in less than a week and 100m in a few months.This course will walk you through:Introduction to Prompt Engineering and its importanceWorking with AI tools such as ChatGPT, Midjourney, GitHub Copilot, GPT-3, DALL-E, and Stable DiffusionUnderstanding the capabilities, limitations, and best practices for each AI toolMastering tokens, log probabilities, and AI hallucinationsGenerating and refining lists, summaries, and role promptingUtilizing AI for sentiment analysis, contextualization, and step-by-step reasoningTechniques for overcoming token limits and meta-promptingAdvanced AI applications, including inpainting, outpainting, and progressive extractionLeveraging AI for real world projects like generating SEO blog articles and stock photosHere's what some students have to say about our Prompt Engineering teaching:"Good information on a fast moving target. Lots of links for further study."“The best parts of the online training were demonstrations and real-life hints. Interesting and useful examples”"Mike is really knowledgeable and really accommodating."So why wait? Boost your career and explore the limitless potential of AI by enrolling in The Complete Prompt Engineering for AI Bootcamp (2023) today!

Overview

Section 1: Five Pillars of Prompting

Lecture 1 What is Prompt Engineering?

Lecture 2 Providing Examples

Lecture 3 Giving Direction

Lecture 4 Adjusting Parameters

Lecture 5 Formatting Responses

Lecture 6 Chaining AIs

Section 2: Intro to ChatGPT

Lecture 7 What is ChatGPT?

Lecture 8 Prompting ChatGPT

Lecture 9 ChatGPT Capabilities and Limitations

Section 3: Intro to Midjourney

Lecture 10 What is Midjourney?

Lecture 11 Prompting Midjourney

Lecture 12 Midjourney Capabilities and Limitations

Section 4: Intro to GitHub Copilot

Lecture 13 What is GitHub Copilot?

Lecture 14 Installing Copilot

Lecture 15 Prompting GitHub Copilot

Lecture 16 GitHub Copilot Capabilities and Limitations

Section 5: Intro to GPT-3

Lecture 17 What is GPT-3?

Lecture 18 Prompting GPT-3

Lecture 19 GPT-3 Capabilities and Limitations

Section 6: Intro to DALL-E 2

Lecture 20 What is DALL-E 2?

Lecture 21 Prompting DALL-E 2

Lecture 22 DALL-E 2 Capabilities and Limitations

Section 7: Intro to Stable Diffusion

Lecture 23 What is Stable Diffusion?

Lecture 24 Prompting Stable Diffusion

Lecture 25 Stable Diffusion Capabilities and Limitations

Section 8: How does AI work?

Lecture 26 What are Tokens?

Lecture 27 Log Probabilities

Lecture 28 AI Hallucinations

Section 9: Standard Text Model Practices

Lecture 29 List Generation

Lecture 30 Advanced List Generation

Lecture 31 Advanced List Generation - Exporting JSON

Lecture 32 Advanced List Generation - Exporting YML

Lecture 33 Sentiment Analysis

Lecture 34 Explain It Like I'm Five

Lecture 35 Least to Most

Lecture 36 Let's Think Step by Step

Lecture 37 Role Prompting

Lecture 38 Ask for Context

Lecture 39 Progressive Summarization

Section 10: Standard Image Model Practices

Lecture 40 Inpainting

Lecture 41 Outpainting

Lecture 42 Style Modifiers

Lecture 43 Quality Boosters

Lecture 44 Weighted Terms

Lecture 45 Negative Prompts

Section 11: Advanced Text Model Techniques

Lecture 46 Overcoming Token Limit - Chunking In ChatGPT

Lecture 47 Overcoming Token Limit - ChatGPT Chunking In Code

Lecture 48 Question Rewriting

Lecture 49 Meta Prompting

Lecture 50 Chain of Thought Reasoning

Lecture 51 Vector Databases

Lecture 52 Reason and Act (ReAct)

Section 12: Advanced Image Model Techniques

Lecture 53 Meme Unbundling

Lecture 54 Dreambooth

Lecture 55 Meme Mapping

Section 13: AI Text Model Projects

Lecture 56 SEO Blog Articles

Lecture 57 Summarizing Text

Lecture 58 Review Classification

Section 14: AI Image Model Projects

Lecture 59 AI Stock Photos

Lecture 60 Making a Brand Logo

Section 15: Conclusion

Lecture 61 AI Resource Hub

Lecture 62 Next steps after the course

Developers interested in AI and hoping to learn how to get more reliable results in production.