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Course Outline
Introduction to Prompt Engineering
- What prompt engineering is and why it matters
- Typical use cases and impact on productivity
- Overview of common model behaviors
Core Principles of Effective Prompts
- Clarity, context, constraints, and examples
- Controlling output length, format, and style
- Common pitfalls and how to avoid them
Prompt Patterns and Templates
- Instruction-based prompts and role prompts
- Chain-of-thought and step-by-step prompting
- Few-shot examples and template reuse
Hands-on Prompting Exercises
- Crafting prompts for summarization and rewriting
- Designing prompts for classification and data extraction
- Live iteration: refining prompts based on outputs
Evaluating and Improving Prompts
- Metrics and heuristics for prompt quality
- Using tests and edge cases to validate prompts
- Versioning and documenting prompt changes
Safety, Bias & Responsible Use
- Recognizing and mitigating biased or unsafe outputs
- Basic guardrails and content constraints
- When to involve human review
Wrap-up, Resources & Next Steps
- Quick reference templates and cheat sheets
- Recommended reading and community resources
- Suggestions for continued practice and learning paths
Requirements
- Familiarity with web-based AI chat interfaces
- Basic understanding of natural language concepts
- Comfort with iterative problem-solving
Audience
- Beginners who want to learn how to communicate effectively with AI models
- Product managers, content creators, and analysts exploring AI tools
- Anyone responsible for producing or evaluating AI-generated content
2 Hours
Testimonials (1)
Very well adjusted
