The Complete Prompt Engineering for AI Bootcamp (2024)
The Complete Prompt Engineering for AI Bootcamp (2024), available at $119.99, has an average rating of 4.5, with 192 lectures, based on 43520 reviews, and has 111314 subscribers.
You will learn about 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. This course is ideal for individuals who are AI power users who want to learn more advanced practices and learn to run Python code to use AI at scale. or Developers interested in AI and hoping to learn how to get more reliable results in production. or AI Engineers who want to keep up with the latest techniques and developments in the industry. It is particularly useful for AI power users who want to learn more advanced practices and learn to run Python code to use AI at scale. or Developers interested in AI and hoping to learn how to get more reliable results in production. or AI Engineers who want to keep up with the latest techniques and developments in the industry.
Enroll now: The Complete Prompt Engineering for AI Bootcamp (2024)
Summary
Title: The Complete Prompt Engineering for AI Bootcamp (2024)
Price: $119.99
Average Rating: 4.5
Number of Lectures: 192
Number of Published Lectures: 192
Number of Curriculum Items: 192
Number of Published Curriculum Objects: 192
Original Price: $49.99
Quality Status: approved
Status: Live
What You Will 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.
Who Should Attend
- 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.
Target Audiences
- 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.
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 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”*
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 3,000 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 (2023) today!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction to the course
Lecture 2: What is Prompt Engineering?
Lecture 3: Accessing resources and prompts
Lecture 4: Optional videos to only do if you know coding
Lecture 5: ChatGPT AI Prompt Pack – 690 Effective Prompts
Lecture 6: Using OpenAI Playground
Chapter 2: Five Principles of Prompting
Lecture 1: Give Direction
Lecture 2: Specify Format
Lecture 3: Provide Examples
Lecture 4: Evaluate Quality
Lecture 5: Divide Labor
Lecture 6: Applying The Five Principles + Worksheet & One Pagers
Chapter 3: How does AI work?
Lecture 1: What are Tokens?
Lecture 2: Log Probabilities
Lecture 3: AI Hallucinations
Chapter 4: Standard Text Model Practices
Lecture 1: List Generation
Lecture 2: Sentiment Analysis
Lecture 3: Explain It Like I'm Five
Lecture 4: Least to Most
Lecture 5: Writing Clear Instructions – Detailed Instructions
Lecture 6: Writing Clear Instructions – Specifying the Steps
Lecture 7: Writing Clear Instructions – Delimiters
Lecture 8: Writing Clear Instructions – Specifying Length
Lecture 9: Let's Think Step by Step
Lecture 10: Role Prompting
Lecture 11: Ask for Context
Lecture 12: Question Rewriting
Lecture 13: Pre-Warming Chats
Lecture 14: Progressive Summarization
Lecture 15: Overcoming the Token Limit in ChatGPT
Lecture 16: Tell me a funny joke
Chapter 5: Advanced Text Model Techniques
Lecture 1: Meta Prompting
Lecture 2: Chain of Thought Reasoning
Lecture 3: Prompt Injection
Lecture 4: Automatic Prompt Engineer
Lecture 5: Github Repository for the Course
Lecture 6: Advanced List Generation – Coding
Lecture 7: Prompt Optimization – Coding
Lecture 8: Overcoming Token Limit – ChatGPT – Managing the Message History – Coding
Lecture 9: Vector Databases – Coding
Lecture 10: Reason and Act (ReAct) – Coding
Lecture 11: Recursive Re-prompting and Revision – Coding
Lecture 12: Information Retrieval with Vector Databases – Coding
Lecture 13: AI Resource Hub
Chapter 6: Deep Dive on LangChain – Coding
Lecture 1: What Is LangChain? – Coding
Lecture 2: Installation – Coding
Lecture 3: Chat Models – Coding
Lecture 4: Chat Prompt Templates – Coding
Lecture 5: Streaming – Coding
Lecture 6: Output Parsers – Coding
Lecture 7: Summarizing Large Amounts of Text – Coding
Lecture 8: Document Loaders, Text Splitting & Creating LangChain Documents – Coding
Lecture 9: Tagging Documents – Coding
Lecture 10: Tracing with LangSmith – Coding
Lecture 11: LangChain Hub – LangSmith – Coding
Lecture 12: LCEL – The Runnable Protocol – Coding
Lecture 13: LCEL – Chat Models, itemgetter & RAG – Coding
Lecture 14: LCEL – Chat Message History & Memory – Coding
Lecture 15: LCEL – Creating Multiple Chains – Coding
Lecture 16: LCEL – Conditional Logic, Branching & Merging – Coding
Lecture 17: Using JSON Mode with LangChain – Coding
Lecture 18: Exercise – Using JSON Mode with LangChain – Coding
Lecture 19: LCEL – with JSON Mode – Coding
Lecture 20: LCEL – with OpenAI Functions & JSON mode – Coding
Lecture 21: Exercise – LCEL – with OpenAI Functions & JSON mode – Coding
Lecture 22: LangChain Vector Databases + the Indexing API – Coding
Lecture 23: LCEL Configurable Fields – Coding
Lecture 24: LangChain Agents & Tools – Coding
Chapter 7: Deep Dive On LangGraph – Coding
Lecture 1: Introduction To LangGraph – Coding
Lecture 2: Simple LangGraph Flows – Coding
Lecture 3: Tool Usage and Persistence – Coding
Lecture 4: Human In The Loop – Coding
Lecture 5: Manually Updating The State – Coding
Lecture 6: Customizing State in LangGraph – Coding
Lecture 7: Time Travel – Coding
Lecture 8: RAG in LangGraph (Self Corrective RAG)
Lecture 9: Extra Content To Explore In Your Own Time (Advanced Branching/Subgraphs – Coding
Chapter 8: Proven Prompting Techniques
Lecture 1: Chain of Thought
Lecture 2: Emotion Prompting
Lecture 3: Role Prompting
Lecture 4: In Context Learning
Lecture 5: Self-Consistency Sampling
Chapter 9: Prompt Optimization & Evals
Lecture 1: What are Evals?
Lecture 2: Prompt Testing in GSheets (without code)
Lecture 3: LLM & Image Model Performance: Advanced Evaluation Strategies – Coding
Lecture 4: Eval for a RAG system
Lecture 5: Prompt Optimization with DSPy – Coding
Lecture 6: Eval metrics with DSPy – Coding
Lecture 7: 1: Prompt Optimization: 5 Principles of Prompting – Coding
Lecture 8: 2: Prompt Optimization: Advanced – Coding
Chapter 10: AI Text Model Projects
Instructors
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Mike Taylor
Prompt Engineer -
James Phoenix
Full Stack Data Engineer
Rating Distribution
- 1 stars: 242 votes
- 2 stars: 482 votes
- 3 stars: 4224 votes
- 4 stars: 17529 votes
- 5 stars: 21166 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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