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Course Outline
Introduction to Prompt Engineering with Ollama
- Understanding Ollama’s capabilities and limitations.
- Principles of prompt engineering.
- Exploring prompt-response dynamics.
Priming and Instruction Design
- Defining role-based instructions.
- Optimizing initial prompts for task-specific outputs.
- Case studies of effective priming.
Chain-of-Thought and Reasoning Prompts
- Encouraging step-by-step reasoning.
- Designing structured logical flows.
- Balancing verbosity and precision.
Prompt Templates and Reusability
- Designing reusable prompt frameworks.
- Dynamic insertion of context.
- Scaling prompt engineering with templates.
Context Window Strategies
- Managing limited context windows.
- Summarization and context reduction.
- Sliding window and memory-based techniques.
Multi-Stage Prompting
- Chaining prompts for complex tasks.
- Building pipelines with intermediate outputs.
- Iterative refinement and feedback loops.
Evaluation and Optimization
- Defining success metrics for prompts.
- Systematic A/B testing of prompt strategies.
- Continuous improvement of prompting methods.
Summary and Next Steps
Requirements
- Basic understanding of large language models.
- Experience with Python programming.
- Familiarity with prompt-based interactions.
Audience
- Prompt engineers.
- Developers.
- Product managers experimenting with Ollama.
14 Hours
