Artificial Intelligence
AI Training
Training
Artificial Intelligence Prompt Engineering (AIPENG)

This workshop is designed to equip learners with the essential skills and advanced techniques required to excel in the field of prompt engineering. The course begins with foundational concepts of AI and Natural Language Processing (NLP), progressing to the principles of crafting effective prompts and understanding AI model responses. Participants will engage in hands-on exercises to practice writing and refining prompts, managing context, and implementing multi-turn strategies that maximize model performance. The course also covers integration of prompt engineering into AI workflows using various tools and platforms. Real-world case studies and best practices will be explored to ensure participants are well-prepared to deploy and maintain AI systems effectively.

About the course

Course Objectives:

By the end of this course the learner will be able to meet these overall objectives:

  • Grasp the basic concepts of Artificial Intelligence and Natural Language Processing, and their relevance to prompt engineering.
  • Develop skills to write clear, concise, and contextually appropriate prompts tailored for various AI applications.
  • Learn techniques to analyze and enhance AI model outputs for accuracy and relevance.
  • Implement strategies such as context management and multi-turn interactions to improve AI performance.
  • Gain proficiency using AI platforms, tools, and APIs for prompt engineering tasks.
Course content

Module 1: Introduction to AI and Prompt Engineering

  • Understanding AI: Definitions and Types
  • Overview of AI Models and Their Applications
  • What is Prompt Engineering?
  • Importance of Prompt Engineering in AI

Module 2: Real-World Applications and Case Studies

  • Case Studies of Successful Prompt Engineering
  • Analyzing Real-World Applications
  • Best Practices for Deployment and Maintenance
  • Hands-on Exercise: Case Study Analysis

Module 3: Basics of Natural Language Processing (NLP)

  • Introduction to NLP
  • Key Concepts in NLP: Tokens, Entities, Sentiment, etc.
  • Understanding the Role of NLP in Prompt Engineering
  • Common NLP Libraries and Tools

Module 4: Crafting Effective Prompts

  • Principles of Writing Effective Prompts
  • Types of Prompts: Informational, Conversational, Instructional
  • Analyzing and Evaluating Prompt Quality
  • Hands-on Exercise: Writing Basic Prompts

Module 5: Understanding AI Model Responses

  • How AI Models Generate Responses
  • Interpreting and Refining Model Outputs
  • Common Challenges in AI Responses
  • Hands-on Exercise: Interpreting AI Responses

Module 6: Tools and Platforms for Prompt Engineering

  • Overview of AI Platforms and Tools (OpenAI, Hugging Face, etc.)
  • Integrating Prompt Engineering into AI Workflows
  • Using APIs and SDKs for Prompt Engineering
  • Hands-on Exercise: Using AI Tools for Prompt Engineering

Module 7: Advanced Prompt Engineering Techniques

  • Context Management in Prompts
  • Multi-turn Prompt Strategies
  • Fine-tuning Prompts for Specific Tasks
  • Hands-on Exercise: Advanced Prompt Crafting

Module 8: Specialized Prompts for Different Domains

  • Domain-Specific Prompt Engineering (Healthcare, Finance, etc.)
  • Ethical Considerations in Prompt Engineering
  • Bias Mitigation in AI Responses
  • Hands-on Exercise: Domain-Specific Prompts