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Duration 14 hours
Course Outline
Introduction to Prompt Engineering with Ollama
- Comprehending 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
- Analyzing case studies of successful priming
Chain-of-Thought and Reasoning Prompts
- Facilitating step-by-step reasoning
- Creating structured logical flows
- Striking a balance between verbosity and precision
Prompt Templates and Reusability
- Developing reusable prompt frameworks
- Integrating dynamic context insertion
- Scaling prompt engineering efforts with templates
Context Window Strategies
- Managing limited context windows
- Techniques for summarization and context reduction
- Utilizing sliding window and memory-based methods
Multi-Stage Prompting
- Linking prompts for intricate tasks
- Constructing pipelines using intermediate outputs
- Applying iterative refinement and feedback loops
Evaluation and Optimization
- Defining success metrics for prompts
- Conducting systematic A/B testing of prompt strategies
- Pursuing continuous improvement in prompting methods
Summary and Next Steps
Requirements
- A foundational understanding of large language models.
- Proficiency in Python programming.
- Familiarity with prompt-based interactions.
Target Audience
- Prompt engineers.
- Developers.
- Product managers exploring Ollama.
