Certified Prompt Engineering — Foundations
What is Artificial Intelligence
Module: AI Foundations
AI is software that performs tasks needing human-like intelligence - understanding language, spotting patterns, and generating content - by learning statistical patterns from huge datasets.
In practice: Ask an AI to 'explain gravity to a 6-year-old' and watch it adapt its language.
Try It Yourself
Ask an AI to 'explain gravity to a 6-year-old' and watch it adapt its language.
Lessons
▶️ 1. What is Artificial Intelligence
▶️ 2. Narrow AI vs General AI
▶️ 3. What is Machine Learning
▶️ 4. What are Large Language Models
▶️ 5. How models are trained
▶️ 6. Tokens and context windows
▶️ 7. Strengths and limits of AI
▶️ 8. AI hallucinations explained
▶️ 9. How LLMs generate text
▶️ 10. Temperature and randomness
▶️ 11. Top-p and sampling
▶️ 12. System, user, and assistant roles
▶️ 13. Why models forget
▶️ 14. Knowledge cutoffs
▶️ 15. Deterministic vs creative tasks
▶️ 16. Multimodal models
▶️ 17. What is a prompt
▶️ 18. The R-C-T-F pattern
▶️ 19. Being specific
▶️ 20. Setting the output format
▶️ 21. Giving context
▶️ 22. Constraints and guardrails
▶️ 23. Common prompt mistakes
▶️ 24. Iterating on prompts
▶️ 25. Role prompting
▶️ 26. Context prompting
▶️ 27. Zero-shot prompting
▶️ 28. Few-shot prompting
▶️ 29. Instruction clarity
▶️ 30. Output templates
▶️ 31. Delimiters and sections
▶️ 32. Asking for reasoning
▶️ 33. Choosing good examples
▶️ 34. Example ordering
▶️ 35. Labelling examples
▶️ 36. How many examples
▶️ 37. Negative examples
▶️ 38. Format-only few-shot
▶️ 39. Dynamic few-shot
▶️ 40. Few-shot pitfalls
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