AI+ Prompting Practitioner™

Course structure

Module 1: Introduction to Prompt Engineering for Developers

• 1.1 Overview of Prompt Engineering
• 1.2 Basics of API Interaction
• 1.3 Understanding Prompt Structures
• 1.4 Case Studies and Best Practices
• 1.5 Hands-on Exercise

Module 2: Advanced Prompt Design and Engineering

• 2.1 Designing Advanced Prompt Techniques
• 2.2 Designing Multi-Turn Interactions
• 2.3 Contextual and Conditional Prompting
• 2.4 Crafting Domain-Specific Prompts
• 2.5 Contextual and Stateful Prompt Engineering
• 2.6 Meta-Prompting and Autonomous Refinement
• 2.7 Hands-on Exercise

Module 3: Experimentation and Optimization

• 3.1 Automated Prompt Optimization Tools
• 3.2 A/B Testing and Evaluation
• 3.3 Reinforcement Learning for Prompt Engineering

Module 4: Designing Advanced Strategies for Prompt Engineering

• 4.1 Contextual and Role-Based Prompting
• 4.2 Adaptive and Multimodal Prompting

Module 5: Integration with Development Tools

• 5.1 Integrating with Popular Development Tools for Prompt
  Engineering
• 5.2 Code Repositories and Templates for Prompt
  Engineering
• 5.3 Developer Communities and Forums for Prompt
  Engineering
• 5.4 Version Control in Prompt Engineering Projects

Module 6: Applications of Prompt Engineering in Various Domains

• 6.1 Natural Language Processing (NLP) Applications using
  Prompt Engineering
• 6.2 Business Applications using Prompt Engineering
• 6.3 Creative Applications using Prompt Engineering

Module 7: Project-Based Learning: Real-World AI Projects Using Prompt Engineering

• 7.1 Project 1: AI-Driven Customer Support
• 7.2 Project 2: Personalized Content Generation
• 7.3 Project 3: AI in Data Analysis

Optional Module: AI Agents for Prompt Engineering

• 1. What Are AI Agents
• 2. Applications and Trends of AI Agents for Prompt Engineers
• 3. Importance of AI Agents
• 4. Types of AI Agents