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Duration 14 hours
Course Outline
Introduction to Prompt Engineering with Ollama
- Analyzing the capabilities and constraints of Ollama
- Core principles of prompt engineering
- Investigating the dynamics between prompts and responses
Priming and Instruction Formulation
- Establishing role-based instructions
- Tuning initial prompts for task-specific results
- Real-world examples of successful priming
Chain-of-Thought and Reasoning Prompts
- Facilitating step-by-step logical reasoning
- Structuring coherent logical flows
- Achieving the right balance between verbosity and precision
Prompt Templates and Reusability
- Creating scalable prompt frameworks
- Implementing dynamic context insertion
- Scaling prompt engineering efforts via templates
Context Window Strategies
- Navigating limited context window constraints
- Applying summarization and context reduction techniques
- Utilizing sliding window and memory-based approaches
Multi-Stage Prompting
- Linking prompts for intricate task execution
- Assembling pipelines with intermediate output stages
- Implementing iterative refinement and feedback cycles
Evaluation and Optimization
- Establishing success metrics for prompt effectiveness
- Conducting systematic A/B testing of prompt strategies
- Driving continuous improvement in prompting methodologies
Summary and Future Steps
Requirements
- Foundational knowledge of large language models
- Proficiency in Python programming
- Familiarity with interacting through prompt-based interfaces
Target Audience
- Prompt engineers
- Software developers
- Product managers exploring Ollama capabilities
