LLM Prompt Engineering
Master prompt‑engineering techniques to control and optimise LLM outputs in real applications.
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Audience: Developers, data scientists, team leads, project managers
Duration: 2 days
Format: Lectures and hands‑on labs (50% – 50%)
Overview
Large Language Models (LLM) are taking the world by storm. This course teaches how to build applications with LLMs, including the basics of LLM scripting and the rules of AI‑use architecture.
Objective
Master prompt‑engineering techniques to control and optimise LLM outputs in real applications.
What You Will Learn
- Formulating effective questions
- Iterative prompt development
- Summarisation techniques
- Inference from prompts
- Task transformation (translate, adjust tone, etc.)
- Expanding LLM interaction
- Building real bots (classification, moderation, chain‑of‑thought reasoning)
- Prompt chaining & output validation
Course Details
Audience: Developers, data scientists, team leads, project managers
Duration: 2 days
Format: Lectures and hands‑on labs (50% – 50%)
- General familiarity with machine learning
Setup: Zero‑install cloud lab • Modern laptop • Chrome browser
Detailed Outline
- What is prompt engineering?
- LLM fundamentals
- Best practices overview
- Common pitfalls
- Crafting effective prompts
- Iterative refinement process
- Testing and validation
- Prompt templates
- Text summarization techniques
- Information extraction
- Sentiment analysis
- Topic classification
- Language translation
- Tone adjustment
- Format conversion
- Content expansion
- Chatbot development
- Chain-of-thought reasoning
- Content moderation
- Classification systems
- Prompt chaining strategies
- Output validation
- Error handling
- Quality assurance
- Hands-on exercises
- Real-world scenarios
- Troubleshooting
- Best practices review
Ready to Get Started?
Contact us to learn more about this course and schedule your training.