All You Need to Know About Prompt Engineering Course Syllabus

Overview: This course provides a comprehensive, hands-on introduction to prompt engineering, covering core techniques, evaluation strategies, and role-specific applications. Designed by MAANG engineers, it blends foundational concepts with practical exercises to build real-world proficiency. With approximately 4 hours of total content, learners engage through interactive quizzes, iterative prompt design, and role-based labs to master effective LLM interaction.

Module 1: Introduction to Prompt Engineering

Estimated time: 0.5 hours

• Definition and evolution of prompt engineering
• Historical context in generative AI development
• Importance of prompts in LLM performance
• Overview of prompt types and use cases

Module 2: Crafting Effective Prompts

Estimated time: 1 hour

• Zero-shot and few-shot prompting techniques
• Chain-of-thought (CoT) prompting
• Structural elements: clarity, specificity, and formatting
• Role prompting and context ordering

Module 3: Techniques & Evaluation

Estimated time: 1 hour

• Advanced techniques: tree-of-thought and templating
• Parameter control for output tuning
• Iterative refinement of prompts
• Evaluation metrics for prompt effectiveness

Module 4: Role-Based Prompt Use Cases

Estimated time: 0.75 hours

• Tailoring prompts for developers
• Prompt frameworks for marketers and educators
• Productivity applications: resumes, emails, interview prep
• Code assistance and task automation prompts

Module 5: Best Practices & Deployment

Estimated time: 0.75 hours

• Data preprocessing for robust prompts
• Handling hallucinations and inaccuracies
• Prompt libraries, reuse, and versioning
• Output validation and performance tracking

Module 6: Final Quiz & Next Steps

Estimated time: 0.25 hours

• Comprehensive quiz on prompt design concepts
• Reflection on key learnings
• Guidance on next projects and portfolio building

Prerequisites

• Familiarity with basic AI and machine learning concepts
• Basic understanding of language models
• Access to an LLM platform for hands-on practice

What You'll Be Able to Do After

• Design effective zero-shot and few-shot prompts
• Apply chain-of-thought and role-based prompting techniques
• Evaluate and refine prompts using performance metrics
• Create reusable prompt templates for various roles
• Build and maintain a versioned prompt library