Artificial Intelligence
Advanced Prompt Engineering
Go from a rough prompt to a professional method: structure your requests (R-C-T-C-O, RTF, CRAFT, RISEN), master advanced techniques (few-shot, chain of thought, personas, chaining), manage tokens and context, choose the right model at the right cost, control the output and use AI responsibly. You leave with a framework, checklists and a reusable prompt.
📋 Course syllabus
INTRODUCTION
1
01 - The promise of the course: prompting, context, models, cost and responsible use
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02 - Who I am and where to follow me
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3
03 - What you get at the end: the framework, the checklists and a reusable prompt
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04 - The roadmap of the 8 modules
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5
05 - Good vs bad prompt: why prompt B wins
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MODULE 1 · HOW AI MODELS WORK
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06 - Module intro: understanding what's behind ChatGPT, Claude and Copilot
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7
07 - What an LLM is, and the difference between tool and model
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8
08 - Temperature: precise or creative
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MODULE 2 · ADVANCED PROMPT ENGINEERING
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09 - Module intro: going from a vague request to a professional prompt
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10
10 - 4 terms: prompt, prompt engineering, specificity, instruction hierarchy
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11
11 - The anatomy of R-C-T-C-O
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12
12 - From a weak prompt to a structured prompt
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13 - Example: a customer email built step by step
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14 - RTF, the minimum for everyday requests
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15
15 - CRAFT and RISEN for richer tasks
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16
16 - Decomposition and iterative improvement
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MODULE 3 · ADVANCED PROMPTING TECHNIQUES
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17 - Module intro: advanced techniques and when to use them
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18
18 - Zero-shot vs few-shot
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19
19 - Negative examples: showing what to avoid
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20
20 - Chain of Thought: reasoning step by step
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21
21 - Personas: giving the AI a point of view
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22 - Prompt chaining: one source, four outputs
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MODULE 4 · SMART TOKEN USAGE & CONTEXT
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23 - Module intro: a conversation is not infinite
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24
24 - Tokens and the context window
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25 - The limits of a conversation, ChatGPT vs Claude
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26 - Memory: conversation, project or account
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27 - Sorting context: essential, optional or noise
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28
28 - The inverted pyramid
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29
29 - Lost in the middle
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30
30 - Delimiters
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31 - Long documents: summarize, select, split, spread out
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32
32 - Chunk & summarize vs targeted extraction
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33
33 - Example: lightening an overloaded prompt
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MODULE 5 · CHOOSING THE RIGHT MODEL & COST
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34 - Module intro: the right tool, the right model, at the right cost
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35
35 - ChatGPT, Claude or Copilot: the differences
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36
36 - The 4 criteria for choosing a model
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37
37 - Which tool for your profile
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38
38 - The multi-model decision framework
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39
39 - Input vs output tokens: which costs more
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40
40 - Managing costs: caching, model choice, output control
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MODULE 6 · ADVANCED OUTPUT CONTROL
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41 - Module intro: deciding the result before the AI writes
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42
42 - The 6 levers to control the response
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43
43 - Behavior constraints vs format constraints
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44
44 - One single instruction for a fully controlled result
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MODULE 7 · RESPONSIBLE & ETHICAL AI
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45 - Module intro: when to verify, and which data to entrust to which account
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46
46 - Hallucinations and their signs
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47
47 - Making the model show its evidence
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48
48 - The 4 safeguards at work
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49
49 - Protecting your data: what "training" means
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50
50 - Each tool's guarantees depending on the account
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51
51 - Individual plan vs enterprise plan
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52
52 - Case: spotting a plausible but unsourced answer
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53
53 - Six real cases: trust or verify?
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MODULE 8 · PUTTING IT ALL TOGETHER
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54 - Module intro: tying everything into a single method
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55
55 - The complete 6-step workflow
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56
56 - Example: from rough notes to an executive brief
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57
57 - Your reusable prompt template
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58
58 - The 4 checklists
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CONCLUSION AND BONUS
59
59 - Glossary (1/2)
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60
60 - Glossary (2/2)
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61
61 - Bonus intro: going further with your tool
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62
62 - Setting up and using ChatGPT, Claude and Copilot well (1/6)
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63
63 - Setting up and using ChatGPT, Claude and Copilot well (2/6)
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64
64 - Setting up and using ChatGPT, Claude and Copilot well (3/6)
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65
65 - Setting up and using ChatGPT, Claude and Copilot well (4/6)
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66
66 - Setting up and using ChatGPT, Claude and Copilot well (5/6)
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67
67 - Setting up and using ChatGPT, Claude and Copilot well (6/6)
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68
68 - 7-day action plan and questions in the comments
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