Prompt Engineering Bootcamp (Working With LLMs): Zero to Mastery

Name: Prompt Engineering Bootcamp (Working With LLMs): Zero to Mastery
Price: 9 USD
Availability: InStock

27h 8m 45s

English

Paid

May 31, 2025

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.

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#	Title	Duration
1	Learn To Work With LLMs with Scott Kerr	01:01
2	Course Introduction	06:20
3	What is Prompt Engineering?	06:25
4	Why is Prompt Engineering Even a Thing?	08:32
5	Breaking GPT	04:03
6	Applied Prompt Engineering	04:25
7	Applied Prompt Engineering with NASA	09:30
8	Why is Prompt Engineering Important to You?	04:07
9	What I'm Using - Part 1	01:22
10	What I'm Using - Part 2 (OpenAI Playground)	04:03
11	Multi-Modality and Tools in LLMs	11:42
12	Getting Started with ChatGPT	01:40
13	The Basics of ChatGPT	04:09
14	ChatGPT App	01:12
15	Optional: ChatGPT Plus	01:56
16	Getting Started with Claude	04:28
17	Project Introduction	02:14
18	Setting Up Your Replit Account	04:45
19	Important Point #1 - Fundamental Truths About LLMs	02:59
20	Important Point #2 - Models are Non-Deterministic	04:04
21	The First Try	04:42
22	Building Our Snake Game - Part 1	06:13
23	Building Our Snake Game - Part 2	05:50
24	Introduction to LLMs	05:45
25	Tokens	05:18
26	Word Guessing Machines?	05:51
27	Thinking Like LLMs - Roll a Dice	06:57
28	Inside LLMs	22:14
29	The Transformer Model	07:39
30	Exercise: Visualize the LLM Architecture	03:57
31	The Training Process	09:58
32	Base Model vs. Assistant Model	07:07
33	Thinking Like LLMs - The Reversal Curse	05:15
34	Artificial General Intelligence (AGI)	05:29
35	Exercise: Use ChatGPT to Read the Research	04:48
36	The World of LLMs	06:06
37	Overview of Our Prompting Framework	03:31
38	The Standard Prompt	04:34
39	Exercise: Get Hyped to Learn!	04:05
40	The Setup	01:02
41	The System Message - Part 1	06:08
42	The System Message - Part 2	05:44
43	Exercise: Strengthen Your System Message	06:43
44	Context - What it Is	05:18
45	Context - The Context Window	09:22
46	Context - Lost in the Middle	11:27
47	Personas and Roles	08:43
48	Personas - Tone, Style and Voice	11:50
49	Custom Instructions	11:15
50	Thinking Like LLMs - Can GPT Keep a Secret?	04:46
51	Exercise: Get ChatGPT to Spill the Tea - Part 1	01:45
52	Exercise: Get ChatGPT to Spill the Tea - Part 2	01:43
53	Exercise: Get ChatGPT to Spill the Tea - Part 3	04:25
54	The User Message	02:10
55	Be Clear and Specific	03:53
56	Delimiters	05:16
57	Exercise: Identify Delimiters	03:26
58	X-Y Problem	06:11
59	In-Context Training	01:02
60	Zero Shot Prompting	01:48
61	One Shot and Few Shot Prompting	09:49
62	Language Models Are Few-Shot Learners	03:49
63	How Many Examples?	02:24
64	Thinking Like LLMs - But Wait...	05:37
65	Chain-of-Thought Prompting - Part 1	05:25
66	Chain-of-Thought Prompting - Part 2	05:46
67	Zero Shot CoT	09:30
68	Exercise: Imposter Syndrome	02:57
69	Career Coach Ideation	07:33
70	The Setup - Persona	06:03
71	The Setup - Context and Commands	05:43
72	The Instructions - Modes	12:21
73	The Instructions - Chain of Thought	03:52
74	The Instructions - Gamify	09:02
75	Meet Your Career Coach	19:54
76	The Output	01:36
77	Length	12:34
78	Formats	07:43
79	Exercise: Output an Excel File	02:31
80	Exercise: Make a Flowchart	04:02
81	Introduction to Guardrails and Jailbreaking	16:33
82	Jailbreak! (The DAN Prompt)	07:26
83	Many Shot Jailbreaking	18:10
84	Prompt Injections - Part 1	09:37
85	Prompt Injections - Part 2	17:43
86	Thinking Like LLMs - Multi-Modal Injection	09:18
87	Leaking - Part 1 (Prompt Leaking)	08:36
88	Leaking - Part 2 (Data Leaking)	18:08
89	Exposure	05:41
90	Poisoning	03:19
91	Toxicity	04:40
92	Hallucinations	13:32
93	Thinking Like LLMs - Big vs Small	18:59
94	Challenge: Conduct Your Own Mechanistic Interpretability Research on Hallucinations	04:35
95	The Model Card	11:06
96	Model Cards Deep Dive	14:44
97	Introduction to Hyperparameters and the OpenAI Playground	03:16
98	Temperature	10:26
99	Top P	04:09
100	Frequency and Presence Penalties	04:39
101	Stop Sequences	05:23
102	Introduction	08:43
103	Custom Instructions	03:14
104	Memory	10:39
105	The Instruction Hierarchy	09:07
106	The Latest: Reasoning Models - Use of Developer Message	11:42
107	The Latest: Research To Prevent ChatGPT from Spilling the Tea	09:28
108	Replay: Multi-Modality and Tools in LLMs	16:47
109	Multi-Modality Deep Dive	01:54
110	Thinking Like LLMs - Attack of the (Voice) Clones	02:42
111	The Bigger Picture	18:23
112	Tools & Function Calling - Part 1	10:30
113	Tools & Function Calling - Part 2	13:43
114	Wrap Up	03:08
115	What Are Open Source LLMs and Why Are They Important?	06:51
116	Chatbot Arena Leaderboard	07:53
117	Battle of the Intelligence Tests	14:39
118	Exercise: Create Your Own Test Prompt (Totem)	01:36
119	Introduction to LMStudio	02:38
120	Setting Up Your Own Model - Part 1	02:52
121	Setting Up Your Own Model - Part 2	09:39
122	Introduction	01:07
123	Auto-Priming	10:51
124	Chain of Density Prompting	18:17
125	Prompt Variables	07:14
126	Prompt Chaining	08:39
127	Prompt Chaining - Programmatic Visualization	17:41
128	Exercise: Prompt Chaining - Customer Support	22:34
129	Thinking Like LLMs - Dark Magic	09:58
130	XML Tags - There's More Than Meets The Eye!	09:18
131	Emotional Stimuli - Part 1	18:37
132	Emotional Stimuli - Part 2	04:43
133	Emotional Stimuli - Part 3 (But Why?)	07:18
134	Self-Consistency	13:45
135	ReAct Prompting	21:35
136	ReAct + CoT-SC	16:48
137	Applied Prompt Engineering with CRISPR - Part 1	13:41
138	Applied Prompt Engineering with CRISPR - Part 2	14:53
139	Tree of Thoughts - Part 1	14:57
140	Tree of Thoughts - Part 2	04:57
141	Tree of Thoughts - Part 3 (ToT via Code)	11:34
142	Tree of Thoughts - Part 4 (ToT via Chaining)	22:12
143	Tree of Thoughts - Part 5 ("Zero Shot" ToT)	12:27
144	Introduction to Prompt Testing	08:33
145	The Importance of Prompt Testing	04:33
146	Thinking Like LLMs - Schrodinger's Prompt	19:18
147	Building a Prompt Test	16:50
148	The Golden Answer	07:01
149	Model Benchmarks	11:29
150	Deep Dive: MMLU Benchmark	14:20
151	Prompt Tests vs. Model Benchmarks?	04:32
152	The Latest: MMLU Pro	18:11
153	Evaluating Results - Human Judge	07:04
154	Evaluating Results - Code Judge	11:24
155	Evaluating Results - AI Judge	22:07
156	Deep Dive: LLMs as a Judge - Biases	22:12
157	Deep Dive: LLMs as a Judge - Prompts	13:02
158	Thinking Like LLMs - Ex Post Facto Reasoning	11:47
159	Here. We. Go!	06:02
160	Introduction to PromptFoo	06:11
161	Our Prompt Testing Framework	04:46
162	Our 1st Prompt Test (Adding Prompts, Metrics + Human Judge) - The Setup	23:10
163	Our 1st Prompt Test (Adding Prompts, Metrics + Human Judge) - The Results	10:21
164	Our 2nd Prompt Test (Adding New Prompts + Code Judge) - The Setup	11:41
165	Our 2nd Prompt Test (Adding New Prompts + Code Judge) - The Results	07:39
166	Our 3rd Prompt Test (Adding 152 Test Cases + AI Judge) - The Setup	25:37
167	Our 3rd Prompt Test (Adding 152 Test Cases + AI Judge) - The Results	08:22
168	Our 4th Prompt Test (Adding Multiple Models) - The Setup	25:59
169	Our 4th Prompt Test (Adding Multiple Models) - The Results	13:12
170	Our 5th Prompt Test (Adding System Messages) - The Setup	24:32
171	Our 5th Prompt Test (Adding System Messages) - The Results	12:23
172	Do You Realize What Just Happened?	04:26
173	Introduction - Through The Looking Glass...	08:41
174	Applied Prompt Engineering with The Turing Test	07:34
175	Mechanistic Interpretability - Part 1	13:25
176	Mechanistic Interpretability - Part 2	21:00
177	Scaling Laws - Model Size	12:56
178	Scaling Laws - Dataset Size	08:05
179	Scaling Laws - Training Compute	11:50
180	Thank You!	01:18
181	Setup Demo: Getting Your API Key	02:24
182	Setup Demo: Downloading AutoGPT	01:04
183	Setup Demo: Installing Docker	03:27
184	Launching Your Autonomous Agent - Part 1	03:26
185	Launching Your Autonomous Agent - Part 2	01:22
186	It's Aliiiiiive! Running Your Autonomous Agent	04:52
187	Task 1: Hello World - Your First Website	16:18
188	Task 2: Python Program - Palindrome Checker	08:41