Prompt Engineering for GenAI Tool

Aim

Program Objectives

Program Structure

Week 1: Fundamentals of Prompt Engineering
Module 1: Introduction to Prompt Engineering

• Chapter 1.1: What is Prompt Engineering?

• Chapter 1.2: The Role of Prompts in Generative AI

• Chapter 1.3: Overview of LLMs (GPT, Claude, Gemini, etc.)

Module 2: Prompt Structure and Core Techniques

• Chapter 2.1: Anatomy of an Effective Prompt

• Chapter 2.2: Instruction-Based vs. Few-Shot Prompts

• Chapter 2.3: Zero-Shot and Chain-of-Thought Prompting

• Chapter 2.4: Prompting for Different Outputs (Text, Code, Image)

Week 2: Applications and Tools in Practice
Module 3: Prompting Across Modalities

• Chapter 3.1: Text Generation, Summarization, and Q&A

• Chapter 3.2: Code Generation and Debugging

• Chapter 3.3: Image Generation (DALL·E, Midjourney, Stable Diffusion)

• Chapter 3.4: Audio and Video AI Prompts (Runway, ElevenLabs)

Module 4: Using Prompt Engineering Tools

• Chapter 4.1: Prompt Playgrounds (OpenAI, Anthropic, Hugging Face)

• Chapter 4.2: Prompt Tuning and Parameter Tweaks

• Chapter 4.3: Versioning and Testing Prompts

• Chapter 4.4: Working with Prompt Templates in APIs & Apps

Week 3: Optimization, Ethics, and Real-World Projects
Module 5: Optimizing and Evaluating Prompts

• Chapter 5.1: Metrics and Benchmarks for Prompt Quality

• Chapter 5.2: Iterative Prompting and A/B Testing

• Chapter 5.3: Safety, Bias, and Hallucination Mitigation

Module 6: Final Projects and Industry Use Cases

• Chapter 6.1: Prompt Engineering for Business Automation

• Chapter 6.2: Capstone – Build Your Prompt-Based Tool or Bot

• Chapter 6.3: Future Trends and Advanced Prompting Techniques

Who Should Enrol?

Program Outcomes

Fee Structure

We accept 20+ global currencies. View list →

What You’ll Gain