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Course Outline
Introduction to Prompt Engineering with Ollama
- Exploring Ollama's capabilities and constraints.
- Core principles of prompt engineering.
- Analyzing prompt-response dynamics.
Priming and Instruction Design
- Establishing role-based instructions.
- Optimizing initial prompts for specific tasks.
- Case studies demonstrating effective priming.
Chain-of-Thought and Reasoning Prompts
- Fostering step-by-step reasoning processes.
- Designing structured logical flows.
- Balancing detail with precision.
Prompt Templates and Reusability
- Developing reusable prompt frameworks.
- Dynamically inserting context.
- Scaling prompt engineering through templates.
Context Window Strategies
- Managing limited context windows.
- Techniques for summarization and context reduction.
- Applying sliding window and memory-based approaches.
Multi-Stage Prompting
- Chaining prompts for complex tasks.
- Creating pipelines with intermediate outputs.
- Implementing iterative refinement and feedback loops.
Evaluation and Optimization
- Defining success metrics for prompts.
- Conducting systematic A/B testing of strategies.
- Continuously improving prompting methods.
Summary and Next Steps
Requirements
- Basic knowledge of large language models.
- Proficiency in Python programming.
- Familiarity with prompt-based interactions.
Target Audience
- Prompt engineers.
- Software developers.
- Product managers exploring Ollama applications.
14 Hours
