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Duration 14 hours
Course Outline
Introduction to Prompt Engineering with Ollama
- Analyzing Ollama’s capabilities and constraints
- Core principles of prompt engineering
- Investigating prompt-response dynamics
Priming and Instruction Design
- Formulating role-based instructions
- Refining initial prompts for task-specific results
- Examining case studies of successful priming
Chain-of-Thought and Reasoning Prompts
- Facilitating step-by-step reasoning processes
- Creating structured logical flows
- Balancing detail with precision
Prompt Templates and Reusability
- Developing reusable prompt frameworks
- Dynamically inserting context variables
- Scaling prompt engineering efforts using templates
Context Window Strategies
- Optimizing within limited context windows
- Applying summarization and context reduction techniques
- Utilizing sliding window and memory-based approaches
Multi-Stage Prompting
- Chaining prompts to address complex tasks
- Constructing pipelines utilizing intermediate outputs
- Implementing iterative refinement and feedback loops
Evaluation and Optimization
- Establishing success metrics for prompts
- Conducting systematic A/B testing of strategies
- Pursuing continuous improvement in prompting methods
Summary and Next Steps
Requirements
- Foundational knowledge of large language models.
- Proficiency in Python programming.
- Experience interacting with prompt-based systems.
Target Audience
- Prompt engineers.
- Software developers.
- Product managers exploring Ollama capabilities.
