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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
- Establishing role-based instructions
- Refining initial prompts for task-specific results
- Examining case studies on effective priming
Chain-of-Thought and Reasoning Prompts
- Facilitating step-by-step reasoning processes
- Structuring logical flows in prompt design
- Striking a balance between verbosity and precision
Prompt Templates and Reusability
- Creating reusable prompt frameworks
- Implementing dynamic context insertion
- Scaling prompt engineering efforts using templates
Context Window Strategies
- Managing constraints of limited context windows
- Applying summarization and context reduction methods
- Utilizing sliding window and memory-based techniques
Multi-Stage Prompting
- Chaining prompts to handle complex tasks
- Constructing pipelines that utilize intermediate outputs
- Implementing iterative refinement and feedback loops
Evaluation and Optimization
- Establishing success metrics for prompt performance
- Conducting systematic A/B testing of prompt strategies
- Pursuing continuous improvement in prompting methods
Summary and Next Steps
Requirements
- Fundamental knowledge of large language models
- Proficiency in Python programming
- Familiarity with prompt-based interactions
Target Audience
- Prompt engineers
- Software developers
- Product managers exploring Ollama capabilities
