Master the Art of Prompt Engineering

Course overview

Course outline

1. 1Day 1: Foundations of Large Language Models (LLMs)

   • Understanding the fundamentals of Large Language Models and Generative AI technologies
   • Exploring the capabilities, limitations, and business applications of LLMs
   • Understanding different language model architectures and their use cases
   • Reviewing autoregressive, transformer-based, and encoder-decoder models
   • Understanding pre-trained, fine-tuned, multilingual, and hybrid AI models
   • Identifying opportunities for AI adoption across business functions and industries
2. 2Day 2: Introduction to Prompt Engineering

   • Understanding the role of prompts in AI interactions and output quality
   • Defining prompt engineering concepts and best practices
   • Exploring the essential components of effective prompts, including instructions, context, inputs, and output requirements
   • Applying common prompt design patterns to improve AI performance
   • Understanding persona-based, audience-focused, and structured interaction approaches
   • Exploring zero-shot, few-shot, and example-based prompting techniques
   • Practical exercises on prompt construction and refinement
3. 3Day 3: Designing High-Performance Prompts

   • Understanding the characteristics of effective and reliable prompts
   • Applying prompt design principles to improve clarity and consistency
   • Establishing performance metrics for evaluating prompt effectiveness
   • Adjusting prompt parameters and settings to optimize outputs
   • Controlling response style, structure, and level of detail
   • Reducing ambiguity, repetition, and undesired model behavior
   • Practical workshop on prompt optimization and performance testing
4. 4Day 4: Advanced Prompt Engineering Techniques

   • Developing reusable prompt frameworks and prompt libraries
   • Understanding semantic search, embeddings, and knowledge retrieval concepts
   • Applying reasoning-oriented prompting techniques to improve problem-solving outcomes
   • Utilizing generated knowledge approaches to enhance response quality
   • Implementing consistency and validation techniques for complex tasks
   • Exploring structured reasoning frameworks and advanced AI interaction strategies
   • Practical exercises on advanced prompt design and testing
5. 5Day 5: Prompt Engineering Applications and Future Trends

   • Applying prompt engineering techniques to business and technical use cases
   • Developing prompts for content generation, summarization, and information analysis
   • Utilizing AI for coding assistance, documentation, and productivity enhancement
   • Understanding ethical considerations, responsible AI use, and governance principles
   • Identifying and troubleshooting common prompt design challenges
   • Exploring emerging trends and future developments in prompt engineering
   • Final project: Designing, testing, and presenting a high-impact prompt solution
   • Course recap, lessons learned, and Q&A session