What will you learn in All You Need to Know About Prompt Engineering Course
Core prompt engineering techniques: Understand prompt types (zero-shot, few-shot, chain-of-thought), prompt structure, and key design elements for guiding LLMs effectively.
Prompt optimization & evaluation: Learn how to craft, iterate, evaluate, and refine prompts—balancing length, clarity, context ordering, and role prompting techniques.
Role & productivity prompts: Apply prompt frameworks for different roles (developer, marketer, educator) and use cases like resume writing, emails, and interviewing
Preprocessing & output validation: Understand how data prep (e.g. examples, formatting) and output evaluation metrics contribute to robust prompt pipelines.
Program Overview
Module 1: Introduction to Prompt Engineering
⏳ ~30 minutes
Topics: Definition, history, importance, and evolution of prompts in generative AI.
Hands-on: Quiz on prompt types, examples, and roles.
Module 2: Crafting Effective Prompts
⏳ ~1 hour
Topics: Types of prompts (zero/few-shot, chain-of-thought), formatting, specificity, and clarity guidelines.
Hands-on: Design multiple prompts for given tasks and compare outputs.
Module 3: Techniques & Evaluation
⏳ ~1 hour
Topics: Techniques like CoT, tree-of-thought, prompt templating, parameter control.
Hands-on: Iteratively refine prompts and assess results across metrics.
Module 4: Role-Based Prompt Use Cases
⏳ ~45 minutes
Topics: Tailoring prompts for productivity—resumes, emails, interview prep, code assistance.
Hands-on: Create role-specific prompt templates and test across LLM responses.
Module 5: Best Practices & Deployment
⏳ ~45 minutes
Topics: Data preparation, handling hallucinations, prompt libraries, reuse, and versioning.
Hands-on: Build a mini prompt library and document prompt variations and performance.
Module 6: Final Quiz & Next Steps
⏳ ~15 minutes
Topics: Consolidation, critical skills, next projects.
Hands-on: Quiz on design concepts and final reflection.
Get certificate
Job Outlook
Emerging LLM specialization: Foundation for roles like Prompt Engineer, AI Product Specialist, and AI-Assisted Developer.
Cross-domain applicability: Useful for devs, PMs, content creators, analysts, educators involving LLM-integrated workflows.
Industry demand: Growing as businesses embed AI into workflows—skilled prompt engineers are in high demand.
Portfolio readiness: Role-based templates and performance metrics provide substantial portfolio or interview-speak examples.
Explore More Learning Paths
Enhance your AI and prompt engineering skills with these carefully selected courses and resources. From mastering ChatGPT prompts to exploring generative AI, these learning paths will help you design better AI interactions and solutions.
Related Courses
Google Prompting Essentials Specialization
Learn essential prompting techniques for Google AI tools and improve your efficiency in generating accurate and useful outputs.Prompt Engineering for ChatGPT
Master the art of designing effective prompts for ChatGPT to get precise, creative, and high-quality AI responses.Generative AI Prompt Engineering Basics
Build a solid foundation in prompt engineering for generative AI, understanding how to guide AI models effectively.
Related Reading
What Is Python Used For
Explore how Python underpins AI tools and supports prompt engineering, connecting programming skills with practical AI applications.
Specification: All You Need to Know About Prompt Engineering Course
|
