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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 (2024) is your one-stop solution to becoming a Prompt Engineer working with cutting-edge AI tools like GPT-4, Stable Diffusion, and GitHub Copilot!
We update the course every month with fresh content (AI moves fast!):
**Updated November 2024 - "Sammo introduction with metaprompting, minibatching and optimization"
**Updated October 2024 - "Anthropic Computer use, Prompt Caching, Perplexity, Langwatch, Zapier"
**Updated September 2024 - "Google NotebookLM, Anthropic Workbench and content updates."
**Updated August, 2024 - "Mixture of Experts, LangGraph and content updates."
**Updated July, 2024 - "Five proven prompting techniques and an advanced prompt optimization case study."
   
**Updated June, 2024 - "LangGraph content including human in the loop, and building a chat bot with LangGraph."
   
**Updated: May, 2024 – "ChatGPT desktop, apps with Flask + HTMX, and prompt optimization DSPy, LM Studio"
**Updated: April, 2024 – "LangChain agents, LCEL, Text-to-speech, Summarizing a whole book, Memetics, Evals, DALL-E"
**Updated: March, 2024 – "More content on vision models, and evaluation as well as reworking old lessons."
**Updated: February, 2024 – "Completely reworked the five principles of prompting + added one pager."
**Updated: January, 2024 – "Added a one-pager graphic and fixed various errors in notebooks."
**Updated: December, 2023 – "Another 10 lessons, including creating an entire ebook and more LCEL."
**Updated: November, 2023 – "10 fresh modules, with 5 covering LangChain Expression Language (LCEL)."
**Updated: October, 2023 – "12 more lessons including GPT-V Vision, Github Co-pilot, LangChain and more."
**Updated: September, 2023 – "10 more lessons, including projects, more LangChain, non-obvious tactics & SDXL."
**Updated: August, 2023 – "10 lessons diving deep into LangChain, plus upgraded 9 lessons from GPT-3 to GPT-4."
**Updated: July, 2023 – "built out the prompt pack, plus 10 more advanced technical lessons added."
**Updated: June 2023 – "added 6 new lessons and 4 more hands-on projects to apply what you learned."
**Updated: May, 2023 – "fixed issues with hard to read text mentioned in reviews, and added 15 more videos."
**Launched: April, 2023
Before we made this course we had both been experimenting with Prompt Engineering since the GPT-3 beta in 2020, and DALL-E beta in 2022, way before ChatGPT exploded on the scene. We slowly replaced every part of our work with AI, and now we work full time in Prompt Engineering. This course is your guide to doing the same and accelerating your career with AI.
*Since launching this course, Mike and James have been commissioned to write a book for O'Reilly titled "Prompt Engineering for Generative AI" which has sold over 3,000 copies!*
If you buy this course you get a PDF of the first chapter free! The book is complementary to the course, but with all new material based on the same principles that work.
Whether you're an aspiring AI Engineer, a developer learning Prompt Engineering, or just a seasoned professional looking to understand what's possible, 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.
! Warning !:
The majority of our lessons require reading and modifying code in Python (for each lesson marked with "- Coding" in the title). Please don't buy this course if you can't code and aren't seriously dedicated to learning technical skills. We've heard from non-technical people they still got value from seeing what's possible, but please don't complain in the reviews ;-)
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 importance
Working with AI tools such as ChatGPT, GPT-4, Midjourney, GitHub Copilot, GPT-4, DALL-E, and Stable Diffusion
Understanding the capabilities, limitations, and best practices for each AI tool
Mastering tokens, log probabilities, and AI hallucinations
Generating and refining lists, summaries, and role prompting
Utilizing AI for sentiment analysis, contextualization, and step-by-step reasoning
Techniques for overcoming token limits and meta-prompting
Advanced AI applications, including inpainting, outpainting, and progressive extraction
Leveraging AI for real world projects like generating SEO blog articles and stock photos
Advanced tooling for AI engineering like Langchain and AUTOMATIC1111
We've had over 3,000 5-Star Reviews!
Here's what some students have to say:
"Practical, fast and yet profound. Super bootcamp." – Barbara Herbst
"This is a very good introduction about how AI can be prompt-engineered. The instructor knows what he's talking about and presents it very clearly." – Eve Sapsford
"Awesome course for beginners and coders alike! Thoroughly enjoyed myself and the guys delivered some great insights, explaining everything in a straight forward way. Would highly recommend to anyone" – Jeremy Griffiths
"This is a very good introduction about how AI can be prompt-engineered. The instructor knows what he's talking about and presents it very clearly." – Hina Josef Teahuahu
"The course is quite detailed, I think almost every topic is covered. I liked the coding parts especially." – Gyanesh Sharma
"Loved how your articulated the value of thoughtfully engineered prompts. The hands-on exercises were insightful." – Akshay Chouksey
"Good content but at few steps voice sounds very robotic, which is funny considering the course is about AI." – Shrish Shrivastava
"Awesome and Detailed Course. Helped a lot to understand the nuances of prompt engineering in AI." – Prasanna Venkatesa Krishnan
“The best parts of the online training were demonstrations and real-life hints. Interesting and useful examples”
"Good" – Jayesh Khandekar
"Mike and James are very good educators and practitioners. Mike also has courses on LinkedIn; together with James, they are running Vexpower. The price is low to collect reviews. It will go up, for sure. GET" – Periklis Papanikolaou
"This course is a legit practical course for prompt engineering, I learned a lot from this course. The resources that they provided is good, but some of the course (tagged with 'Coding' in the Course Title) is for intermediate or advance people in Python programming. If you are not usual with Python, this will be a challenge (like me), but we can overcome it because they taught us step by step pretty clearly (of course I need to pause or backwards). Thanks for this course, but you guys can provide more real case scenario when using AI (less/without coding maybe...)" – J Arnold Parlindungan Gultom
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!
Who this course is for:
AI power users who want to learn more advanced practices and learn to run Python code to use AI at scale.
Developers interested in AI and hoping to learn how to get more reliable results in production.
AI Engineers who want to keep up with the latest techniques and developments in the industry.

What you'll learn

Learn the strengths and weaknesses of ChatGPT, Midjourney, GitHub Copilot, Stable Diffusion & other major models.

Recognize the "Five Principles of Prompting", as well as common tips & tricks for professional grade output.

Apply what you’ve learned to generate new AI products in 15+ real-world projects for both text and image generation use cases.

Understand the Python coding patterns and tooling you need to run and scale AI reliably in production, and start working as an AI Engineer.

Requirements

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Introduction
6
1.1-Introduction to the course
1.2-What is Prompt Engineering?
1.3-Accessing resources and prompts
1.4-Optional videos to only do if you know coding
1.5-ChatGPT AI Prompt Pack - 690 Effective Prompts
1.6-Using OpenAI Playground
2-Five Principles of Prompting
6
2.1-Give Direction
2.2-Specify Format
2.3-Provide Examples
2.4-Evaluate Quality
2.5-Divide Labor
2.6-Applying The Five Principles + Worksheet & One Pagers
3-How does AI work?
3
3.1-What are Tokens?
3.2-Log Probabilities
3.3-AI Hallucinations
4-Standard Text Model Practices
15
4.1-List Generation
4.2-Sentiment Analysis
4.3-Explain It Like I'm Five
4.4-Least to Most
4.5-Writing Clear Instructions - Detailed Instructions
4.6-Writing Clear Instructions - Specifying the Steps
4.7-Writing Clear Instructions - Delimiters
4.8-Writing Clear Instructions - Specifying Length
4.9-Let's Think Step by Step
4.10-Role Prompting
4.11-Ask for Context
4.12-Question Rewriting
4.13-Pre-Warming Chats
4.14-Progressive Summarization
4.15-Overcoming the Token Limit in ChatGPT
5-Advanced Text Model Techniques
18
5.1-Meta Prompting
5.2-Chain of Thought Reasoning
5.3-Prompt Injection
5.4-Automatic Prompt Engineer
5.5-Github Repository for the Course
5.6-Advanced List Generation - Coding
5.7-Prompt Optimization - Coding
5.8-Overcoming Token Limit - ChatGPT - Managing the Message History - Coding
5.9-Vector Databases - Coding
5.10-Reason and Act (ReAct) - Coding
5.11-Recursive Re-prompting and Revision - Coding
5.12-Information Retrieval with Vector Databases - Coding
5.13-Structured Outputs for OpenAI - Coding
5.14-What is Prompt Caching?
5.15-Prompt Caching in Practice - Coding
5.16-OpenAI Realtime - Example
5.17-AI Resource Hub
5.18-Personas of Thought
6-Deep Dive on LangChain - Coding
24
6.1-What Is LangChain? - Coding
6.2-Installation - Coding
6.3-Chat Models - Coding
6.4-Chat Prompt Templates - Coding
6.5-Streaming - Coding
6.6-Output Parsers - Coding
6.7-Summarizing Large Amounts of Text - Coding
6.8-Document Loaders, Text Splitting & Creating LangChain Documents - Coding
6.9-Tagging Documents - Coding
6.10-Tracing with LangSmith - Coding
6.11-LangChain Hub - LangSmith - Coding
6.12-LCEL - The Runnable Protocol - Coding
6.13-LCEL - Chat Models, itemgetter & RAG - Coding
6.14-LCEL - Chat Message History & Memory - Coding
6.15-LCEL - Creating Multiple Chains - Coding
6.16-LCEL - Conditional Logic, Branching & Merging - Coding
6.17-Using JSON Mode with LangChain - Coding
6.18-Exercise - Using JSON Mode with LangChain - Coding
6.19-LCEL - with JSON Mode - Coding
6.20-LCEL - with OpenAI Functions & JSON mode - Coding
6.21-Exercise - LCEL - with OpenAI Functions & JSON mode - Coding
6.22-LangChain Vector Databases + the Indexing API - Coding
6.23-LCEL Configurable Fields - Coding
6.24-LangChain Agents & Tools - Coding
7-Deep Dive On LangGraph - Coding
9
7.1-Introduction To LangGraph - Coding
7.2-Simple LangGraph Flows - Coding
7.3-Tool Usage and Persistence - Coding
7.4-Human In The Loop - Coding
7.5-Manually Updating The State - Coding
7.6-Customizing State in LangGraph - Coding
7.7-Time Travel - Coding
7.8-RAG in LangGraph (Self Corrective RAG)
7.9-Extra Content To Explore In Your Own Time (Advanced Branching/Subgraphs - Coding
8-Proven Prompting Techniques
5
8.1-Chain of Thought
8.2-Emotion Prompting
8.3-Role Prompting
8.4-In Context Learning
8.5-Self-Consistency Sampling
9-Prompt Optimization & Evals
11
9.1-What are Evals?
9.2-Prompt Testing in GSheets (without code)
9.3-LLM & Image Model Performance: Advanced Evaluation Strategies - Coding
9.4-Eval for a RAG system
9.5-Prompt Optimization with DSPy - Coding
9.6-Eval metrics with DSPy - Coding
9.7-1: Prompt Optimization: 5 Principles of Prompting - Coding
9.8-2: Prompt Optimization: Advanced - Coding
9.9-Sammo - Introduction
9.10-Sammo - Metaprompting
9.11-Sammo - Testing and Optimization
10-AI Text Model Projects
21
10.1-Tell me a funny joke
10.2-Create an Entire Ebook
10.3-SEO Blog Articles
10.4-Thought Leadership Posts
10.5-Summarizing Text - Coding
10.6-Summarizing An Entire Book - Coding
10.7-Review Classification - Coding
10.8-AI Blog Post Generation - Coding
10.9-Text To Speech using OpenAI - Coding
10.10-Using LangChain + Llama3 Locally with LMStudio - Coding
10.11-Transcribing audio from a Youtube Video - Coding
10.12-Fine-Tuning on Writing Style - Coding
10.13-Adcopy Writing - Coding
10.14-Social Media Posting - Coding
10.15-Reverse Engineering a Publication - Coding
10.16-Building a GPT wrapper with Flask and HTMX - Coding
10.17-Qualitative Analysis- Coding
10.18-Claim Detection - Coding
10.19-Summarize a news story
10.20-Write a PRD
10.21-OpenAI Realtime - Twilio Example
11-Standard Image Model Practices
9
11.1-Style Modifiers
11.2-Quality Boosters
11.3-Negative Prompts
11.4-Weighted Terms
11.5-Prompt Rewriting
11.6-Inpainting
11.7-Outpainting
11.8-Realistic Models
11.9-Consistent Characters
12-Advanced Image Model Techniques
18
12.1-Midjourney Outpainting (Zoom Out / Pan)
12.2-Midjourney Inpainting (Vary Region)
12.3-Meme Unbundling
12.4-Meme Mapping
12.5-Permutations Prompts
12.6-Prompt Reverse-Engineering
12.7-Prompt Token Analysis
12.8-AUTOMATIC1111 - Requires Automatic1111
12.9-X/Y/Z Prompt Grids - Requires Automatic1111
12.10-Advanced Inpainting - Requires Automatic1111
12.11-ControlNet - Requires Automatic1111
12.12-ControlNet Inpainting - Requires Automatic1111
12.13-Segment Anything - Requires Automatic1111
12.14-Textual Inversion - Coding
12.15-Dreambooth - Coding
12.16-Migrating to Stable Diffusion XL in AUTOMATIC1111 - Coding
12.17-Comfy UI
12.18-Beta - Anthropic Computer Use - Example
13-AI Image Model Projects
7
13.1-AI Custom Illustrations
13.2-Making a Brand Logo
13.3-AI Stock Photos
13.4-Runway - Creating b-roll footage
13.5-Product Placement - Coding
13.6-Tagging Ad Creative - Coding
13.7-AI Profile Picture - Coding
14-Deep Dive on ChatGPT
13
14.1-What is ChatGPT?
14.2-Prompting ChatGPT
14.3-ChatGPT Capabilities and Limitations
14.4-ChatGPT Shortcuts
14.5-ChatGPT Custom Instructions
14.6-ChatGPT - DALL-E 3
14.7-ChatGPT+ (Code Execution, DALLE, GPTs & Web Browsing Functionality)
14.8-ChatGPT - GPT-V (Vision)
14.9-ChatGPT - Interactive Tables
14.10-ChatGPT - Canvas
14.11-ChatGPT - Desktop Application (MacOS only)
14.12-GPT Store - Building Custom GPTs - Coding
14.13-ChatGPT Search
15-Deep Dive on GPT-4
3
15.1-What is GPT-4?
15.2-Prompting GPT-4
15.3-GPT-4 Capabilities and Limitations
16-Deep Dive on Midjourney v6
3
16.1-What is Midjourney?
16.2-Prompting Midjourney
16.3-Midjourney Capabilities and Limitations
17-Deep Dive on Anthropic Claude
4
17.1-What is Claude?
17.2-Prompting Claude
17.3-Claude Projects
17.4-Anthropic Workbench
18-Deep Dive on Stable Diffusion XL
3
18.1-What is Stable Diffusion?
18.2-Prompting Stable Diffusion - Coding
18.3-Stable Diffusion Capabilities and Limitations
19-Deep Dive on DALL-E 3
3
19.1-What is DALL-E 3?
19.2-Prompting DALL-E 3
19.3-DALL-E 3 Capabilities and Limitations
20-Deep Dive on GitHub Copilot - Coding
6
20.1-What is GitHub Copilot? - Coding
20.2-Installing Copilot - Coding
20.3-Prompting GitHub Copilot - Coding
20.4-GitHub Copilot Capabilities and Limitations - Coding
20.5-Github Copilot - Editing Features - Coding
20.6-Github Copilot Chat + Custom Prompts
21-Multimodal Models
4
21.1-Vision Prompting Guide
21.2-Automating Product Descriptions via GPT-V
21.3-Automating UX Landing Page Analysis via GPT-V
21.4-Memetic Analysis with GPT-V
22-Agent Architectures - Coding
2
22.1-Mixture of Experts - Aggregator
22.2-Additional Agent Architectures
23-Deep Dive on other AI Models
13
23.1-What is Google Gemini?
23.2-What is Meta LLaMA?
23.3-Runway ML
23.4-What is Microsoft 'New' Bing?
23.5-What is Tencent ARC?
23.6-What is Google Vision?
23.7-What is OpenAI Whisper?
23.8-What is Falcon?
23.9-Text Generation WebUI - Coding
23.10-What is Mistral 7B?
23.11-Testing Open-Source Models
23.12-What is Flux?
23.13-Perplexity Search
24-AI Tools we've tried
7
24.1-PromptLayer
24.2-PromptFoo
24.3-Instructor
24.4-Google NotebookLM
24.5-Groq Cloud
24.6-Zapier (no code)
24.7-Langwatch
25-Conclusion
3
25.1-Free PDF Prompt Engineering Book (CH01)
25.2-Sources of Inspiration
25.3-Next steps after the course

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