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Duration 14 hours
Course Outline
Foundational Prompt Engineering with Ollama
- Assessing the strengths and constraints of Ollama.
- Core principles behind prompt engineering.
- Analyzing the dynamics between prompts and responses.
Priming and Instruction Formulation
- Establishing role-based directives.
- Refining initial prompts to achieve task-specific results.
- Examining case studies of successful priming strategies.
Chain-of-Thought and Reasoning Frameworks
- Facilitating step-by-step logical reasoning.
- Creating structured logical pathways.
- Striking a balance between detail and accuracy.
Prompt Templates and Reusability
- Developing reusable prompt structures.
- Implementing dynamic context integration.
- Scaling prompt engineering efforts via templates.
Strategies for Context Window Management
- Navigating the limitations of fixed context windows.
- Employing summarization and context reduction techniques.
- Applying sliding window and memory-based approaches.
Multi-Stage Prompting Architectures
- Linking prompts to address complex objectives.
- Constructing pipelines that leverage intermediate outputs.
- Implementing iterative refinement and feedback mechanisms.
Assessment and Optimization
- Establishing key performance indicators for prompts.
- Conducting systematic A/B tests on different prompt strategies.
- Continuously enhancing prompting methodologies.
Conclusion and Future Directions
Requirements
- Foundational knowledge of large language models.
- Proficiency in Python programming.
- Familiarity with interacting via prompts.
Target Audience
- Prompt engineers.
- Software developers.
- Product managers exploring Ollama capabilities.
