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
0/4
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.
0/3
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
0/4
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
0/3
Design an end-to-end prompt solution for
Documentation of Prompt Logic
Presentation & Evaluation
Prompt Engineering

Structured Prompting for Complex Problems

In this lesson, you will learn how to solve complex tasks using structured prompts — and when not to use chain-of-thought reasoning.

Many AI errors happen because prompts are overloaded with multiple actions like calculate, compare, analyze, and explain at the same time. When instructions are unclear, steps may be skipped.

You will learn a simple professional framework:

  1. Understand the problem

  2. List the steps

  3. Solve step by step

  4. Give the final answer last

This structure improves clarity, logic, and accuracy.

🎯 What You Will Learn

  • Why complex prompts confuse AI

  • How multi-action questions cause skipped steps

  • A simple structured approach for complex tasks

  • Real example: discount calculation problem

  • When not to use chain-of-thought reasoning

  • How to balance clarity and efficiency

👥 Who This Lesson Is For

Prompt engineering beginners, AI students, developers, business professionals, educators, and anyone solving multi-step problems with AI.

🌍 Practical Applications

  • Financial calculations (discount, tax, profit)

  • Business decision analysis

  • Data comparison

  • Coding logic breakdown

  • Project planning

  • Multi-step math problems

💼 Career Relevance

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

Professionals who design clear thinking processes get more reliable AI outputs.

Exercise Files
LMS-PE-M5 – L2.pdf
Size: 3.94 MB
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