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Course Outline
Introduction to Prompt Engineering
- Understanding what prompt engineering is and its significance
- Common use cases and its impact on productivity
- Overview of typical 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
- Fundamental understanding of natural language concepts
- Comfort with iterative problem-solving
Target Audience
- Beginners seeking to improve their communication with AI models
- Product managers, content creators, and analysts exploring AI tools
- Anyone tasked with producing or evaluating AI-generated content
7 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
Since we had a Roche internal AI Training (6 lections), the presented majority content was a good sum-up, however, personally I did learn something new in this training session, which was to counter back the prompt, so the AI program has to ask you about possible questions regarding to this specific topic.
