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Duration 14 hours
Course Outline
Introduction to Prompt Engineering with Ollama
- Gaining insight into Ollama’s capabilities and constraints
- Core principles of prompt engineering
- Analyzing the dynamics of prompt and response interactions
Priming and Instructional Design
- Establishing role-based directives
- Optimizing initial prompts to yield task-specific results
- Reviewing case studies of successful priming strategies
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
- Creating reusable prompt frameworks
- Dynamically injecting contextual information
- Scaling prompt engineering efforts through templating
Context Window Strategies
- Navigating the constraints of limited context windows
- Applying summarization and context reduction techniques
- Utilizing sliding window and memory-based methods
Multi-Stage Prompting
- Linking prompts to address complex tasks
- Constructing pipelines that leverage intermediate outputs
- Refining processes through iterative feedback loops
Evaluation and Optimization
- Establishing key performance indicators for prompts
- Conducting systematic A/B testing of different prompt strategies
- Pursuing continuous improvement in prompting methodologies
Summary and Future Directions
Requirements
- Fundamental knowledge of large language models
- Proficiency in Python programming
- Experience with prompt-driven interactions
Target Audience
- Prompt engineers
- Software developers
- Product managers exploring the capabilities of Ollama
