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Duration 14 hours
Course Outline
Fundamentals of Prompt Engineering with Ollama
- Analyzing the strengths and constraints of Ollama
- Core principles underpinning prompt engineering
- Investigating the dynamics between prompts and responses
Priming and Instructional Design
- Establishing role-based directive instructions
- Tuning initial prompts for task-specific accuracy
- Examining case studies on successful priming methods
Chain-of-Thought and Logical Reasoning
- Fostering step-by-step analytical reasoning
- Architecting structured logical progressions
- Striking a balance between detail and conciseness
Prompt Templates and Reusability
- Developing scalable prompt frameworks
- Integrating dynamic context elements
- Scaling engineering efforts through template utilization
Context Window Management Strategies
- Navigating the constraints of limited context windows
- Applying summarization and context compression techniques
- Implementing sliding window and memory-based approaches
Multi-Stage Prompting Architectures
- Sequencing prompts for complex task resolution
- Creating pipelines with intermediate processing stages
- Employing iterative refinement and feedback mechanisms
Assessment and Performance Optimization
- Establishing key performance indicators for prompts
- Conducting systematic A/B testing of prompt variations
- Pursuing continuous enhancement of prompting methodologies
Recap and Future Directions
Requirements
- Foundational knowledge of large language models
- Proficiency in Python programming
- Prior experience with prompt-driven interactions
Target Audience
- Prompt engineers
- Software developers
- Product managers exploring Ollama capabilities