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Duration 14 hours
Course Outline
Introduction to Prompt Engineering with Ollama
- Grasping Ollama’s strengths and boundaries
- Core principles of prompt engineering
- Analyzing the dynamics between prompts and responses
Priming and Instruction Design
- Creating role-based directives
- Tuning initial prompts for specific task outcomes
- Reviewing case studies of successful priming techniques
Chain-of-Thought and Reasoning Prompts
- Facilitating step-by-step logical reasoning
- Structuring coherent logical flows
- Achieving a balance between detail and precision
Prompt Templates and Reusability
- Developing reusable prompt frameworks
- Incorporating dynamic context insertion
- Scaling prompt engineering efforts through templates
Context Window Strategies
- Navigating limited context window constraints
- Applying summarization and context reduction techniques
- Implementing sliding window and memory-based approaches
Multi-Stage Prompting
- Linking prompts to address complex tasks
- Creating pipelines utilizing intermediate outputs
- Employing iterative refinement and feedback cycles
Evaluation and Optimization
- Establishing success metrics for prompt effectiveness
- Conducting systematic A/B testing of various strategies
- Pursuing continuous improvement in prompting methodologies
Summary and Next Steps
Requirements
- A foundational understanding of large language models
- Practical experience with Python programming
- Familiarity with prompt-based interaction methods
Target Audience
- Prompt engineers
- Developers
- Product managers exploring the capabilities of Ollama
