This course offers a practical and in-depth introduction to Prompt Engineering — a crucial skill for interacting effectively with generative AI tools like ChatGPT. Over two focused modules, learners will explore prompt types, advanced techniques, ethical implications, and real-world applications of crafting prompts. Ideal for developers, content creators, analysts, and anyone looking to harness the power of AI more intelligently and creatively. Includes hands-on activities and refinement practice to build mastery.

Intended audience

Prompt Engineer, AI Specialist, AI Content Creator, Product Manager (AI), Technical Writer (AI Tools)

Prerequisites

Open to all

Assessment & certification

Assessment fee: Included — no extra fee
Assessment mode: Online proctored
Assessment type: MCQ
Certificate provider: Prompt Engineer, AI Specialist, AI Content Creator, Product Manager (AI), Technical Writer (AI Tools)

Syllabus

Week 1: Module 1: Introduction to Prompt Engineering
Week 2: What is prompt engineering and its importance in AI
Week 3: Why it matters for GenAI tools and use cases
Week 4: Module 2: Fundamentals of AI Language Models
Week 5: Understanding language models (e.g., GPT-4, BERT)
Week 6: How they process input: tokenization, neural networks, training
Week 7: Role of prompts in guiding output
Week 8: Module 3: Types of Prompts
Week 9: Open-ended vs. structured prompts
Week 10: Examples and use cases
Week 11: Outcome expectations based on prompt style
Week 12: Module 4: Crafting Effective Prompts
Week 13: Prompt design principles: clarity, specificity, structure
Week 14: Avoiding ambiguity and confusing inputs
Week 15: Examples: Good vs. bad prompts
Week 16: Module 5: Hands-on Prompt Writing
Week 17: Prompt creation for summarization, translation, and code generation
Week 18: Group evaluation of AI outputs and prompt effectiveness
Week 19: Module 6: Recap and Q&A
Week 20: Key takeaways
Week 21: Clarifications and discussion
Week 22: Module 7: Advanced Prompting Techniques
Week 23: Few-shot, zero-shot, and chain-of-thought prompting
Week 24: Context-aware and memory-based approaches
Week 25: Instruction-style prompts for tasks
Week 26: Module 8: Fine-Tuning for Outcomes
Week 27: Improving creative and technical outputs
Week 28: Iterative prompt refinement and feedback
Week 29: A/B testing prompts for optimization
Week 30: Module 9: Ethics and Bias
Week 31: Detecting and understanding AI bias
Week 32: Writing inclusive and responsible prompts
Week 33: Ethical do’s and don’ts
Week 34: Module 10: Advanced Prompting Practice
Week 35: Apply learned techniques to a live use-case (e.g., chatbot, blog, idea generator)
Week 36: Iteration based on feedback
Week 37: Peer review and discussion