Mímir, Keeper of the Well of Wisdom
The Complete Prompt Engineering for AI Bootcamp (2025)
https://www.udemy.com/course/prompt-engineering-for-ai/
Year : 2025
Language : English
Level : All Levels
Category : Development
Subcategory : Software Development Tools
Duration : 24h 6m
Lectures : 237
Rating : 4.5/5 (124,418 reviews)
Students : 304,148
INSTRUCTOR(S)
HEADLINE
Learn practical coding skills for working professionally with
AI, including GPT-5, Veo3, Midjourney, & GitHub Copilot.
WHAT YOU'LL LEARN
* Learn the strengths and weaknesses of ChatGPT, GPT-5,
Midjourney, GitHub Copilot, Veo3 & 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 20+
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
* Python Coding Required
WHO IS THIS COURSE 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.
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 (2025) is your one-stop solution to becoming a Prompt
Engineer working with cutting-edge AI tools like GPT-5, Veo3,
Midjourney, and GitHub Copilot! We update the course regularly
with fresh content (AI moves fast!): **Updated August 2025 -
"Google Veo3 full module (7 lessons), plus a one hour DSPy
session with the Every team" **Updated July 2025 - "ChatGPT -
Chat Models vs Reasoning Models, ChatGPT - Study and learn,
ChatGPT - Agent Mode" **Updated June 2025 - " Flux Kontext
image
editing, Advanced Consistent Characters, ControlNet, Fine-
Tuning
with Lora" **Updated May 2025 - "Run Flux AI through Fal, Text
to Image as well as Inpainting and Outpainting" **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 5,000
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-5, Midjourney, GitHub
Copilot, Veo3, and other top models 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 DSPy We've had over 40,000 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
(2025) today!
COURSE CONTENT
Chapter 1: Introduction
1. Introduction to the Course
2. What is Prompt Engineering?
3. Accessing Resources and Prompts
4. Optional Videos to only do if you Know Coding
5. ChatGPT AI Prompt Pack - 705 Effective Prompts
6. Github Repository for the Course - Coding
7. AI Resource Hub
8. Curriculum Overview
Chapter 2: Five Principles of Prompting
9. Give Direction
10. Specify Format
11. Provide Examples
12. Evaluate Quality
13. Divide Labor
14. Applying The Five Principles + Worksheet & One Pagers
Chapter 3: How Does AI Work?
15. What are Tokens?
16. AI Hallucinations
17. Chat Models vs Reasoning Models
Chapter 4: Deep Dive on ChatGPT
18. What is ChatGPT?
19. Prompting ChatGPT
20. ChatGPT - Capabilities and Limitations
21. ChatGPT - Search
22. ChatGPT - Deep Research
23. ChatGPT - Data Analysis
24. ChatGPT - Interactive Tables
25. ChatGPT - Image Generation
26. ChatGPT - Agent Mode
27. ChatGPT - Custom Instructions
28. ChatGPT - Shortcuts
29. ChatGPT - Canvas
30. ChatGPT - Memory
31. ChatGPT - Scheduled Tasks
32. ChatGPT - Vision
33. Vision Prompting Guide
34. ChatGPT - Desktop Application
35. ChatGPT - Study & Learn
36. GPT Store - Building Custom GPTs - Coding
Chapter 5: Standard Text Model Practices
37. Role Prompting
38. Different Output Formats
39. Least to Most
40. Explain It Like I'm Five
41. Meta Prompting
42. Overcoming the Maximum Token Output Length
43. Sentiment Analysis
44. Writing Clear Instructions - Detailed Instructions
45. Writing Clear Instructions - Specifying the Steps
46. Writing Clear Instructions - Delimiters
47. Writing Clear Instructions - Specifying Length
48. Let's Think Step by Step
49. Ask for Context
50. Pre-Warming Chats
51. Overcoming the Token Limit in ChatGPT
52. Prompt Injection - Coding
53. Automatic Prompt Engineer - Coding
Chapter 6: OpenAI Features & Functionality - Coding
54. OpenAI Features - Coding
55. Setting up an OpenAI Account & API Key - Coding
56. Using OpenAI Playground - Coding
57. Exploring OpenAI's Platform - Coding
58. Responses API & Messages - Coding
59. Coding Notebook with Different OpenAI Services - Coding
60. How to Count Tokens using tiktoken - Coding
61. Managing The Message History - Coding
62. What is Streaming? - Coding
63. Rate Limits, Retrying and How to Overcome These Problems
64. Chat Completions vs Responses API - Coding
65. Tool (Function) Calling
66. Building a Simple Agent with Tools
67. Parallelization of requests with Async OpenAI
Chapter 7: Embeddings and Vector Databases - Coding
68. Understanding Vector Embeddings
69. Information Retrieval with Vector Databases - Coding
70. Vector Databases with Pinecone - Coding
71. RAG with Supabase PGVector - Coding
Chapter 8: Advanced Text Model Techniques - Coding
72. Role Prompting - Coding
73. Emotion Prompting - Coding
74. Chain of Thought - Coding
75. In Context Learning - Coding
76. Self-Consistency Sampling - Coding
77. Reason and Act (ReAct) - Coding
78. Personas of Thought - Coding
79. Prompt Optimization - Coding
80. Structured Outputs for OpenAI - Coding
81. What is Prompt Caching? - Coding
82. Prompt Caching in Practice - Coding
83. OpenAI Realtime - Example - Coding
Chapter 9: Deep Dive on LangChain - Coding
84. What Is LangChain? - Coding
85. Installation - Coding
86. Chat Models - Coding
87. Chat Prompt Templates - Coding
88. Streaming - Coding
89. Output Parsers - Coding
90. Summarizing Large Amounts of Text - Coding
91. Document Loaders, Text Splitting & Creating LangChain
Documents - Coding
92. Tagging Documents - Coding
93. Tracing with LangSmith - Coding
94. LangChain Hub - LangSmith - Coding
95. LCEL - The Runnable Protocol - Coding
96. LCEL - Chat Models, itemgetter & RAG - Coding
97. LCEL - Chat Message History & Memory - Coding
98. LCEL - Creating Multiple Chains - Coding
99. LCEL - Conditional Logic, Branching & Merging - Coding
100. LangChain Vector Databases + the Indexing API - Coding
101. LCEL Configurable Fields - Coding
102. LangChain Agents & Tools - Coding
Chapter 10: Deep Dive On LangGraph - Coding
103. Introduction To LangGraph - Coding
104. Simple LangGraph Flows - Coding
105. Tool Usage and Persistence - Coding
106. Human In The Loop - Coding
107. Manually Updating The State - Coding
108. Customizing State in LangGraph - Coding
109. Time Travel - Coding
110. RAG in LangGraph (Self Corrective RAG)
111. Extra Content To Explore In Your Own Time (Advanced
Branching/Subgraphs - Coding
Chapter 11: AI Text Model Projects
112. Progressive Summarization
113. Tell me a funny joke
114. Create an Entire Ebook
115. SEO Blog Articles
116. Thought Leadership Posts
117. Summarizing An Entire Book - Coding
118. Review Classification - Coding
119. AI Blog Post Generation - Coding
120. Text To Speech using OpenAI - Coding
121. Using LangChain + Llama3 Locally with LMStudio - Coding
122. Transcribing audio from a Youtube Video - Coding
123. Fine-Tuning on Writing Style - Coding
124. Social Media Posting - Coding
125. Reverse Engineering a Publication - Coding
126. Building a GPT wrapper with Flask and HTMX - Coding
127. Qualitative Analysis- Coding
128. Claim Detection - Coding
129. Summarize a news story
130. Write a PRD
131. OpenAI Realtime - Twilio Example - Coding
132. Automating Product Descriptions via GPT-V - Coding
133. Automating UX Landing Page Analysis via GPT-V - Coding
134. Memetic Analysis with GPT-V
Chapter 12: Deep Dive on Midjourney v6
135. What is Midjourney?
136. Prompting Midjourney
137. Midjourney Capabilities and Limitations
Chapter 13: Standard Image Model Practices
138. Style Modifiers
139. Negative Prompts
140. Weighted Terms
141. Realistic Models
142. Midjourney Inpainting (Vary Region)
143. Midjourney Outpainting (Zoom Out / Pan)
144. Consistent Characters
145. Permutations Prompts
146. Prompt Reverse-Engineering
147. Prompt Token Analysis
148. Meme Unbundling
Chapter 14: Advanced Image Generation Techniques
149. Fal AI Playground
150. Text to Image with Flux
151. Async Text to Image with Flux
152. X/Y/Z Prompt Grids
153. Image Upscaling with Clarity
154. Image to Image with Flux
155. Image Editing with Flux.Kontext
156. Advanced Inpainting with Flux
157. Draw Image Mask with Gradio
158. Segment Anything Masking
159. Advanced Outpainting with Flux
160. Advanced Consistent Characters
161. ControlNet with Flux Pro
162. Fine-Tuning with Flux Lora
163. Image to Video with Kling AI
164. AUTOMATIC1111 - Setting up a WebUI for Stable Diffusion
- Coding
165. Migrating to Stable Diffusion XL in AUTOMATIC1111 -
Coding
166. Comfy UI
Chapter 15: AI Image Model Projects
167. AI Custom Illustrations
168. Making a Brand Logo
169. AI Stock Photos
170. Runway - Creating b-roll footage
171. Product Placement - Coding
172. Tagging Ad Creative - Coding
173. AI Profile Picture - Coding
Chapter 16: Deep Dive on Stable Diffusion XL
174. What is Stable Diffusion?
175. Prompting Stable Diffusion - Coding
176. Stable Diffusion Capabilities and Limitations
Chapter 17: Prompt Optimization & Evals
177. What are Evals (Evaluations)?
178. Prompt Testing in GSheets (without code)
179. Eval for a RAG system (special guest*)
180. Prompt Optimization with DSPy - Coding
181. Eval metrics with DSPy - Coding
182. Prompt Optimization: 5 Principles of Prompting - Coding
183. Prompt Optimization: Advanced - Coding
184. Sammo - Introduction - Coding
185. Sammo - Metaprompting - Coding
186. Sammo - Testing and Optimization - Coding
187. DSPy Primer (with the Every team)
188. LLM & Image Model Performance: Advanced Evaluation
Strategies - Coding
Chapter 18: Agent Architectures - Coding
189. Prompt Chaining
190. Routing
191. Parallelization
192. LLM Orchestrators
193. Agents
194. Mixture of Experts - Aggregator
195. Evaluator Optimizer
196. Additional Agent Architectures
Chapter 19: Deep Dive on Anthropic Claude
197. What is Claude?
198. Prompting Claude
199. Claude Projects
200. Anthropic Workbench
Chapter 20: Deep Dive on Google Veo3
201. What is Google Veo3?
202. Prompting Google Veo3 in Flow
203. JSON Prompting Veo3
204. Multi-Shot Prompting with Veo3
205. Frames to Video in Google Flow
206. Ingredients to Video in Google Flow
207. Spatial Prompting with Annotated Frames using Veo3
Chapter 21: Deep Dive on DALL-E 3
208. What is DALL-E 3?
209. Prompting DALL-E 3
210. DALL-E 3 Capabilities and Limitations
Chapter 22: Deep Dive on other AI Models
211. What is Google Gemini?
212. Gemini 2.0 Native Image Generation
213. Google Gemini - Deep Research
214. What is Meta LLaMA?
215. Runway ML
216. What is Google Vision?
217. What is OpenAI Whisper?
218. Testing Open-Source Models
219. What is Flux?
Chapter 23: AI Tools We've Tried
220. Google NotebookLM
221. PromptLayer
222. PromptFoo
223. Langwatch
224. Instructor
225. Groq Cloud
226. Zapier (no code)
227. Perplexity Search
228. Beta - Anthropic Computer Use - Example
Chapter 24: Deep Dive on GitHub Copilot - Coding
229. What is GitHub Copilot? - Coding
230. Installing Copilot - Coding
231. Prompting GitHub Copilot - Coding
232. GitHub Copilot Capabilities and Limitations - Coding
233. Github Copilot - Editing Features - Coding
234. Github Copilot Chat + Custom Prompts
Chapter 25: Conclusion
235. Free PDF Prompt Engineering Book (CH01)
236. Sources of Inspiration
237. Next steps after the course
DATES
Published : 2023-04-04
Last Updated : 2025-08-24
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