The Complete Prompt Engineering for AI Bootcamp (2025)
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Introduction
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Five Principles of Prompting
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How Does AI Work?
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Deep Dive on ChatGPTWhat is ChatGPT?Prompting ChatGPTChatGPT – Capabilities and LimitationsChatGPT – SearchChatGPT – Deep ResearchChatGPT – Data AnalysisChatGPT – Interactive TablesChatGPT – Image GenerationChatGPT – Custom InstructionsChatGPT – ShortcutsChatGPT – CanvasChatGPT – MemoryChatGPT – Scheduled TasksChatGPT – VisionVision Prompting GuideChatGPT – Desktop ApplicationGPT Store – Building Custom GPTs – Coding
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Standard Text Model PracticesRole PromptingDifferent Output FormatsLeast to MostExplain It Like I’m FiveMeta PromptingOvercoming the Maximum Token Output LengthSentiment AnalysisWriting Clear Instructions – Detailed InstructionsWriting Clear Instructions – Specifying the StepsWriting Clear Instructions – DelimitersWriting Clear Instructions – Specifying LengthLet’s Think Step by StepAsk for ContextPre-Warming ChatsOvercoming the Token Limit in ChatGPTPrompt Injection – CodingAutomatic Prompt Engineer – Coding
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OpenAI Features & Functionality – CodingOpenAI Features – CodingSetting up an OpenAI Account & API Key – CodingUsing OpenAI Playground – CodingExploring OpenAI’s Platform – CodingResponses API & Messages – CodingCoding Notebook with Different OpenAI Services – CodingHow to Count Tokens using tiktoken – CodingManaging The Message History – CodingWhat is Streaming? – CodingRate Limits, Retrying and How to Overcome These ProblemsChat Completions vs Responses API – CodingTool (Function) CallingBuilding a Simple Agent with ToolsParallelization of requests with Async OpenAI
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Embeddings and Vector Databases – Coding
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Advanced Text Model Techniques – CodingRole Prompting – CodingEmotion Prompting – CodingChain of Thought – CodingIn Context Learning – CodingSelf-Consistency Sampling – CodingReason and Act (ReAct) – CodingPersonas of Thought – CodingPrompt Optimization – CodingStructured Outputs for OpenAI – CodingWhat is Prompt Caching? – CodingPrompt Caching in Practice – CodingOpenAI Realtime – Example – Coding
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Deep Dive on LangChain – CodingWhat Is LangChain? – CodingInstallation – CodingChat Models – CodingChat Prompt Templates – CodingStreaming – CodingOutput Parsers – CodingSummarizing Large Amounts of Text – CodingDocument Loaders, Text Splitting & Creating LangChain Documents – CodingTagging Documents – CodingTracing with LangSmith – CodingLangChain Hub – LangSmith – CodingLCEL – The Runnable Protocol – CodingLCEL – Chat Models, itemgetter & RAG – CodingLCEL – Chat Message History & Memory – CodingLCEL – Creating Multiple Chains – CodingLCEL – Conditional Logic, Branching & Merging – CodingLangChain Vector Databases + the Indexing API – CodingLCEL Configurable Fields – CodingLangChain Agents & Tools – Coding
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Deep Dive On LangGraph – CodingIntroduction To LangGraph – CodingSimple LangGraph Flows – CodingTool Usage and Persistence – CodingHuman In The Loop – CodingManually Updating The State – CodingCustomizing State in LangGraph – CodingTime Travel – CodingRAG in LangGraph (Self Corrective RAG)Extra Content To Explore In Your Own Time (Advanced Branching/Subgraphs – Coding
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AI Text Model ProjectsProgressive SummarizationTell me a funny jokeCreate an Entire EbookSEO Blog ArticlesThought Leadership PostsSummarizing An Entire Book – CodingReview Classification – CodingAI Blog Post Generation – CodingText To Speech using OpenAI – CodingUsing LangChain + Llama3 Locally with LMStudio – CodingTranscribing audio from a Youtube Video – CodingFine-Tuning on Writing Style – CodingSocial Media Posting – CodingReverse Engineering a Publication – CodingBuilding a GPT wrapper with Flask and HTMX – CodingQualitative Analysis- CodingClaim Detection – CodingSummarize a news storyWrite a PRDOpenAI Realtime – Twilio Example – CodingAutomating Product Descriptions via GPT-V – CodingAutomating UX Landing Page Analysis via GPT-V – CodingMemetic Analysis with GPT-V
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Deep Dive on Midjourney v6
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Standard Image Model Practices
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Deep Dive on Stable Diffusion XL
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Advanced Image Model Techniques
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AI Image Model Projects
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Prompt Optimization & EvalsWhat are Evals (Evaluations)?Prompt Testing in GSheets (without code)LLM & Image Model Performance: Advanced Evaluation Strategies – CodingEval for a RAG system (special guest*)Prompt Optimization with DSPy – CodingEval metrics with DSPy – CodingPrompt Optimization: 5 Principles of Prompting – CodingPrompt Optimization: Advanced – CodingSammo – Introduction – CodingSammo – Metaprompting – CodingSammo – Testing and Optimization – Coding
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Agent Architectures – Coding
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Deep Dive on Anthropic Claude
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Deep Dive on DALL-E 3
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Deep Dive on other AI Models
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AI Tools We’ve Tried
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Deep Dive on GitHub Copilot – Coding
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Conclusion
Are you eager to dive into the world of AI and master the art of Prompt Engineering? The Complete Prompt Engineering for AI Bootcamp (2025) 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 regularly with fresh content (AI moves fast!):
**Updated April 2025 – “Responses API: Refreshed the OpenAI, embeddings section. Re-filmed 40+ videos. New intro video with up to date cuts and better opening”
**Updated March 2025 – “Added optimizer-evaluator pattern and re-filmed up old videos.”
**Updated February 2025 – “Added new models and tools like deep research and native image gen.”
**Updated January 2025 – “Added Agent Architectures, Memory + Scheduled Tasks in ChatGPT.”
**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 4,000 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:
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Introduction to Prompt Engineering and its importance
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Working with AI tools such as ChatGPT, GPT-4, Midjourney, GitHub Copilot, GPT-4, DALL-E, and Stable Diffusion
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Understanding the capabilities, limitations, and best practices for each AI tool
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Mastering tokens, log probabilities, and AI hallucinations
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Generating and refining lists, summaries, and role prompting
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Utilizing AI for sentiment analysis, contextualization, and step-by-step reasoning
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Techniques for overcoming token limits and meta-prompting
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Advanced AI applications, including inpainting, outpainting, and progressive extraction
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Leveraging AI for real world projects like generating SEO blog articles and stock photos
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Advanced tooling for AI engineering like Langchain and AUTOMATIC1111
We’ve had over 30,000 5-Star Reviews!
Here’s what some students have to say:
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“Practical, fast and yet profound. Super bootcamp.” – Barbara Herbst
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“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
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“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
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“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
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“The course is quite detailed, I think almost every topic is covered. I liked the coding parts especially.” – Gyanesh Sharma
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“Loved how your articulated the value of thoughtfully engineered prompts. The hands-on exercises were insightful.” – Akshay Chouksey
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“Good content but at few steps voice sounds very robotic, which is funny considering the course is about AI.” – Shrish Shrivastava
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“Awesome and Detailed Course. Helped a lot to understand the nuances of prompt engineering in AI.” – Prasanna Venkatesa Krishnan
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“The best parts of the online training were demonstrations and real-life hints. Interesting and useful examples”
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“Good” – Jayesh Khandekar
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“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
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“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 (2025) today!
What's included
- 22.5 hours on-demand video
- 2 articles
- 95 downloadable resources
- Access on mobile and TV
- Certificate of completion