Introduction to LLM and Prompt Engineering #
This page is a structured learning template. Replace the comments with clear explanations, examples, formulas, diagrams, and practical insights while keeping the Hugo shortcodes intact.
Learning Objectives #
- Explain what a large language model is and how it is used for language tasks.
- Describe the role of instructions, context, examples, and output constraints in prompts.
- Compare zero-shot, one-shot, and few-shot prompting.
- Recognise when structured reasoning or generated knowledge may improve a response.
Chapter Map #
| Section | Topic | Status |
|---|---|---|
| 1 | Introduction to Large Language Models | ☐ |
| 2 | Introduction to Prompt Engineering | ☐ |
| 3 | N-shot Prompting | ☐ |
| 4 | Chain-of-Thought Prompting | ☐ |
| 5 | Generated Knowledge Prompting | ☐ |
Big Picture #
1. Introduction to Large Language Models ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
2. Introduction to Prompt Engineering ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
3. N-shot Prompting ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
4. Chain-of-Thought Prompting ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
5. Generated Knowledge Prompting ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
Practical Exploration #
Design and compare prompts for classification, extraction, summarisation, and question answering.
# Add a minimal, well-commented Python example here.
Comparison Table #
| Concept or Model | Main Idea | Strength | Limitation | Typical Use |
|---|---|---|---|---|
Common Mistakes #
Practice Questions #
Key Takeaways #
Understanding Checklist #
- I can explain Introduction to Large Language Models without referring to notes.
- I can explain Introduction to Prompt Engineering without referring to notes.
- I can explain N-shot Prompting without referring to notes.
- I can explain Chain-of-Thought Prompting without referring to notes.
- I can explain Generated Knowledge Prompting without referring to notes.