Master Proven Techniques to Design, Tune, and Evaluate High-Performing Prompts for LLMs
Sub Category
- Data Science
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Objectives
- Discover the core principles of prompt engineering and why structured prompting leads to more consistent LLM outputs
- Explore best practices and reusable templates that simplify prompt creation across use cases
- Master foundational prompting frameworks like Chain-of-Thought, Step-Back, Role Prompting, and Self-Consistency.
- Apply advanced strategies such as Chain-of-Density, Tree-of-Thought, and Program-of-Thought to handle complex reasoning and summarization tasks.
- Design effective prompts that align with different task types—classification, generation, summarization, extraction, etc.
- Tune hyperparameters like temperature, top-p, and frequency penalties to refine output style, diversity, and length.
- Control model responses using max tokens and stop sequences to ensure outputs are task-appropriate and bounded.
- Implement prompt tuning workflows to improve model performance without retraining the base model.
- Evaluate prompt effectiveness using structured metrics and tools like PromptFoo for A/B testing and performance benchmarking.
Pre Requisites
- No prior experience or technical skills are required—just bring your curiosity, a computer with internet access, and an interest in exploring AI prompting.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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