Course Content
Introduction to Prompt Engineering
• What is Prompt Engineering? • Why prompts matter in AI systems • How Large Language Models (LLMs) work (high-level) • Prompt vs traditional programming • Real-world applications (education, coding, marketing, design) Outcome: Understand the role of prompts in AI interaction
0/5
What is Prompt?
12:49
How Large Language Models (LLMs) work (high-level)
07:15
Prompt vs traditional programming
07:44
Real-world applications (education, coding, marketing, design)
09:08
Introduction to Prompt Engineering
Fundamentals of Prompts
• What is a prompt? • Types of prompts: o Question-based o Instruction-based o Command-based o Context-based • Prompt structure: o Instruction o Context o Input data o Output format Hands-on: Writing simple prompts and observing responses
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Types of prompts
09:52
Types of Prompts & Prompt Structure
Prompt Components & Best Practices
• Clarity and specificity • Tone and role assignment • Constraints and boundaries • Formatting prompts (lists, tables, JSON, markdown) • Avoiding ambiguity Hands-on: Improve weak prompts into strong prompts
0/3
Clarity, specificity, Tone&Role And Constrains
06:06
Formatting prompts And Avoiding ambiguity
05:44
Prompt Components & Best Practices
Prompting Techniques
• Zero-shot prompting • One-shot prompting • Few-shot prompting • Role prompting (e.g., “Act as a teacher…”) • Step-by-step prompting Hands-on: Compare outputs using different techniques
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Zero-shot, One-shot, Few-shot Prompting Techniques
05:29
Role prompting And Step-by-step prompting
05:08
CaseStudy
07:44
Prompt Engineering – Prompting Techniques Quiz
Chain-of-Thought & Reasoning
Chain-of-Thought Prompting is a technique where we ask AI to explain its reasoning step by step before giving the final answer. It improves clarity, reduces mistakes, and works best for complex problems that require logical thinking.
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What is chain-of-thought prompting?
06:47
Breaking complex problems into steps
06:37
Chain-of-Thought Prompting & Structured Reasoning
Prompt Engineering for Specific Use Cases
0/4
Real-World Prompting: Education, Content & Coding
05:53
Chain of Thought Prompting for Real-World Tasks
05:10
Mini Project
04:52
Prompt Engineering for Specific Use Cases
Advanced Prompt Engineering
0/5
Prompt templates
Prompt Iteration and Refinement
System vs user prompts (conceptual)
Multi-Step Workflows
Prompt chaining
Evaluation & Optimization
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Measuring prompt effectiveness
Reducing Hallucinations
Controlling Verbosity and Creativity
Handling Edge Cases and Failures
Ethics, Safety & Limitations
• Bias in AI responses • Responsible prompting • Data privacy considerations • Limitations of LLMs • Human-in-the-loop concept
0/5
Bias in AI responses
Responsible prompting
Data Privacy Considerations
Limitations of LLMs
Human-in-the-loop Concept
Capstone Project
• Design an end-to-end prompt solution for: o Chatbot o Learning assistant o Content generator o Coding helper • Documentation of prompt logic • Presentation & evaluation
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Design an end-to-end prompt solution for
Documentation of Prompt Logic
Presentation & Evaluation
Prompt Engineering

Chain of Thought Prompting (Step-by-Step Guide)

In this lesson, we explore one of the most powerful techniques in prompt engineering — Chain of Thought Prompting.

Instead of asking AI for a direct answer, you guide it to explain its reasoning step by step before concluding. This simple change improves clarity, accuracy, and reliability.

Using easy real-world examples like math and reasoning tasks, you’ll see how structured prompts lead to better AI responses.

🎯 What You Will Learn

  • What chain of thought prompting means

  • Why AI sometimes produces incorrect answers

  • How step-by-step reasoning reduces errors

  • How to modify prompts for logical clarity

  • When to use structured prompting

👥 Who This Lesson Is For

AI beginners, students, teachers, developers, content creators, and anyone who wants more accurate AI outputs.

🌍 Practical Applications

  • Solving math problems

  • Logical reasoning tasks

  • Coding explanations

  • Business and financial analysis

  • Data interpretation

💼 Career Relevance

Structured prompting is valuable in AI, automation, data analysis, software development, marketing, and education.

Learning to guide AI reasoning improves both productivity and professional credibility.

Exercise Files
LMS-PE-M5- L1.pdf
Size: 3.94 MB
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