English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 123 Lessons (14h 24m) | 3.28 GB
Stop memorizing random prompts. Instead, learn how Large Language Models (LLMs) actually work and how to use them effectively. This course will take you from beginner to mastering LLMs by teaching you how to create your own AI tools that will take your career to the next level.
Learn how to work with LLMs and AI. We guarantee you that this is the most comprehensive and up-to-date prompt engineering bootcamp course. You’re going to learn the skills needed to be in the top 10% of using AI in the real world.
WHAT YOU’LL LEARN
- Learn the fundamentals of prompting and its practical applications, including real-world examples from NASA
- Gain practical experience and a deeper understanding of how LLMs work (and how they don’t) through hands-on exercises
- Learn to use leading closed-source LLMs like GPT and Claude and even set up your own open-source LLMs
- Master empirically-proven prompting techniques to improve the effectiveness and utility of your interactions with LLMs
- Apply your skills in real-world scenarios through numerous guided and unguided projects that teach you to apply your skills
- Stay updated with the latest advancements in AI and prompt engineering, with continuous course updates to ensure you are always at the cutting edge
Table of Contents
1 Learn To Work With LLMs with Scott Kerr
2 Course Introduction
3 What is Prompt Engineering_
4 Why is Prompt Engineering Even a Thing_
5 Breaking GPT
6 Applied Prompt Engineering
7 Applied Prompt Engineering with NASA
8 Why is Prompt Engineering Important to You_
9 What I’m Using – Part 1
10 What I’m Using – Part 2 (OpenAI Playground)
11 Multi-Modality and Tools in LLMs
12 Getting Started with ChatGPT
13 The Basics of ChatGPT
14 ChatGPT App
15 Optional ChatGPT Plus
16 Project Introduction
17 Setting Up Your Replit Account
18 The First Try
19 Building Our Snake Game – Part 1
20 Building Our Snake Game – Part 2
21 Introduction to LLMs – Part 1
22 Introduction to LLMs – Part 2
23 Tokens
24 Word Guessing Machines_
25 Thinking Like LLMs – Roll a Dice
26 Inside LLMs
27 The Transformer Model
28 Exercise Visualize the LLM Architecture
29 The Training Process
30 Base Model vs. Assistant Model
31 Thinking Like LLMs – The Reversal Curse
32 Artificial General Intelligence (AGI)
33 Exercise Use ChatGPT to Read the Research
34 The World of LLMs
35 Overview of Our Prompting Framework
36 The Standard Prompt
37 Exercise Get Hyped to Learn!
38 The Setup
39 The System Message – Part 1
40 The System Message – Part 2
41 Exercise Strengthen Your System Message
42 Context – What it Is
43 Context – The Context Window
44 Context – Lost in the Middle
45 Personas and Roles
46 Personas – Tone, Style and Voice
47 Custom Instructions
48 Thinking Like LLMs – Can GPT Keep a Secret_
49 Exercise Get ChatGPT to Spill the Tea – Part 1
50 Exercise Get ChatGPT to Spill the Tea – Part 2
51 Exercise Get ChatGPT to Spill the Tea – Part 3
52 The User Message
53 Be Clear and Specific
54 Delimiters
55 Exercise Identify Delimiters
56 X-Y Problem
57 In-Context Training
58 Zero Shot Prompting
59 One Shot and Few Shot Prompting
60 Language Models Are Few-Shot Learners
61 How Many Examples_
62 Thinking Like LLMs – But Wait…
63 Chain-of-Thought Prompting – Part 1
64 Chain-of-Thought Prompting – Part 2
65 Zero Shot CoT
66 Exercise Imposter Syndrome
67 Career Coach Ideation
68 The Setup – Persona
69 The Setup – Context and Commands
70 The Instructions – Modes
71 The Instructions – Chain of Thought
72 The Instructions – Gamify
73 Meet Your Career Coach
74 The Output
75 Length
76 Formats
77 Exercise Output an Excel File
78 Exercise Make a Flowchart
79 Jailbreak!
80 Thinking Like LLMs – Prompt Injection
81 Introduction to Hyperparameters and the OpenAI Playground
82 Temperature
83 Top P
84 Frequency and Presence Penalties
85 Stop Sequences
86 Setup Demo Getting Your API Key
87 Setup Demo Downloading AutoGPT
88 Setup Demo Installing Docker
89 Launching Your Autonomous Agent – Part 1
90 Launching Your Autonomous Agent – Part 2
91 It’s Aliiiiiive! Running Your Autonomous Agent
92 Task 1 Hello World – Your First Website
93 Task 2 Python Program – Palindrome Checker
94 What Are Open Source LLMs and Why Are They Important_
95 Chatbot Arena Leaderboard
96 Battle of the Intelligence Tests
97 Exercise Create Your Own Test Prompt (Totem)
98 Introduction to LMStudio
99 Setting Up Your Own Model – Part 1
100 Setting Up Your Own Model – Part 2
101 Introduction
102 Auto-Priming
103 Chain of Density Prompting
104 Prompt Variables
105 Prompt Chaining
106 Prompt Chaining – Programmatic Visualization
107 Exercise Prompt Chaining – Customer Support
108 Thinking Like LLMs – Dark Magic
109 XML Tags – There’s More Than Meets The Eye!
110 Emotional Stimuli – Part 1
111 Emotional Stimuli – Part 2
112 Emotional Stimuli – Part 3 (But Why_)
113 Self-Consistency
114 ReAct Prompting
115 ReAct + CoT-SC
116 Applied Prompt Engineering with CRISPR – Part 1
117 Applied Prompt Engineering with CRISPR – Part 2
118 Tree of Thoughts – Part 1
119 Tree of Thoughts – Part 2
120 Tree of Thoughts – Part 3 (ToT via Code)
121 Tree of Thoughts – Part 4 (ToT via Chaining)
122 Tree of Thoughts – Part 5 (_Zero Shot_ ToT)
123 Thank You!
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