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
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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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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
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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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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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Prompt Engineering for Specific Use Cases
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Advanced Prompt Engineering
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Evaluation & Optimization
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Ethics, Safety & Limitations
• Bias in AI responses
• Responsible prompting
• Data privacy considerations
• Limitations of LLMs
• Human-in-the-loop concept
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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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