Prompt Engineering Masterclass
Intermediate Level
Master the art of crafting effective prompts for LLMs and generative AI
Course Overview
- •Understanding the fundamentals of prompt engineering
- •Prompt design principles for different LLM architectures
- •Advanced techniques for complex reasoning tasks
- •Prompt optimization and evaluation methodologies
- •Developing prompts for multi-modal AI systems
- •Building reliable and robust prompt templates for production
Course Modules
Foundations of Prompt Engineering
1 weekTopics Covered
- Evolution of LLMs and prompt sensitivity
- Key components of effective prompts
- Role specification and context setting
- Instruction clarity and formatting best practices
- Understanding token limitations and optimization
Assignments
- Baseline prompt effectiveness analysis
- Comparative study of prompt variations
Instructor
Nim Hewage
Co-founder & AI Strategy Consultant
Over 13 years of experience implementing AI solutions across Global Fortune 500 companies and startups. Specializes in enterprise-scale AI transformation, MLOps architecture, and AI governance frameworks.
Prerequisites
- Basic understanding of natural language processing concepts
- Familiarity with large language models (LLMs)
- Experience using ChatGPT, Claude, or similar AI assistants
- Basic programming knowledge (Python recommended)
- No advanced technical skills required, but practical experience with AI tools is helpful
What You'll Learn
- Design effective prompts for various LLM applications
- Implement advanced techniques like few-shot learning and chain-of-thought prompting
- Systematically evaluate and optimize prompt performance
- Create robust prompt templates for enterprise use cases
- Apply prompt engineering to multi-modal AI systems
- Implement safety measures and guardrails for responsible AI use
Certification
Prompt Engineering Certification
Upon successful completion of the course and all assignments, participants will receive a verified certificate in Advanced Prompt Engineering.
Complete all module assignments and the final capstone project with a score of 75% or higher.
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