Course Curriculum: Prompt Engineering

Course Curriculum: Prompt Engineering (Beginner → Advanced)

🎯 Course Objective

Enable learners to design, optimize, and evaluate prompts for Large Language Models (LLMs) to solve real-world problems in coding, data analysis, education, business, and automation.

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🧩 Module 1: Foundations of Prompt Engineering

Learning Outcomes

• Understand how LLMs work

• Learn why prompts matter

Topics

• What is Generative AI?

• How LLMs (GPT, Claude, Gemini) work (tokens, context, probability)

• Prompt Engineering vs traditional programming

• Limitations & hallucinations

• Prompt lifecycle

Hands-On

• Basic prompts vs refined prompts

• Observe output differences

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🧩 Module 2: Prompt Basics & Syntax

Topics

• Prompt structure

  • Instruction

  • Context

  • Input data

  • Output format

• Zero-shot prompting

• Role-based prompting

• Constraints and formatting rules

Examples

• “Act as a…”

• Output as JSON, table, bullet points

Practice

• Rewrite weak prompts into strong ones

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🧩 Module 3: Prompt Patterns & Techniques

Topics

• Few-shot prompting

• Chain-of-Thought (CoT)

• Step-by-step reasoning

• Self-consistency prompting

• Deliberate prompting

Practice

• Math reasoning prompts

• Logical decision prompts

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🧩 Module 4: Advanced Prompting Strategies

Topics

• Prompt decomposition

• Prompt chaining

• Recursive prompting

• Tree-of-Thoughts (ToT)

• ReAct (Reason + Act)

Use Cases

• Multi-step problem solving

• Complex planning tasks

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🧩 Module 5: Prompt Engineering for Coding

Topics

• Code generation prompts

• Debugging prompts

• Code explanation prompts

• Refactoring prompts

• Test case generation

Tools

• Python, Java, JavaScript examples

• AI pair-programming

Project

• Build a coding assistant prompt

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🧩 Module 6: Prompt Engineering for Data & Analytics

Topics

• Data cleaning prompts

• SQL generation prompts

• Excel & CSV analysis

• Visualization prompts

• Insight extraction

Practice

• Analyze datasets using prompts

• Generate charts and summaries

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🧩 Module 7: Prompt Engineering for Content & Education

Topics

• Blog writing prompts

• SEO-optimized prompts

• Lesson planning prompts

• Quiz & exam generation

• Personalized tutoring prompts

Practice

• Create an AI tutor prompt

• Generate adaptive learning content

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🧩 Module 8: Prompt Engineering for Business & Productivity

Topics

• Email drafting prompts

• Resume & interview prompts

• Marketing copy prompts

• Customer support prompts

• Decision-making prompts

Mini Project

• Build a business workflow prompt

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🧩 Module 9: Prompt Optimization & Evaluation

Topics

• Prompt testing methods

• A/B testing prompts

• Reducing hallucinations

• Bias & ethical considerations

• Cost and token optimization

Practice

• Improve accuracy of failing prompts

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🧩 Module 10: System Prompts & AI Agents

Topics

• System vs user prompts

• Memory & context control

• Tool-calling prompts

• Autonomous agents

• Prompt frameworks (LangChain concepts)

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🧩 Module 11: Security, Ethics & Safety

Topics

• Prompt injection attacks

• Jailbreak prompts

• Data privacy

• Responsible AI usage

• Prompt hardening techniques

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🧩 Module 12: Capstone Project

Project Options

• AI Tutor Prompt System

• Coding Assistant Prompt

• Data Analysis Prompt Pipeline

• Business Automation Prompt

Deliverables

• Prompt documentation

• Test cases

• Performance evaluation

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📜 Certification Criteria (Optional)

• Quiz after each module

• Final capstone evaluation

• Prompt portfolio submission

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🛠 Tools Covered

• ChatGPT / GPT-4+

• Claude

• Gemini

• OpenAI Playground

• Prompt testing tools

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📈 Skill Level Mapping

• Beginner → Modules 1–3

• Intermediate → Modules 4–7

• Advanced → Modules 8–12

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💡 Bonus Add-Ons (Optional)

• Prompt Engineering for AI APIs

• Prompt Engineering for Autonomous Apps

• AI + Prompt Engineering Freelancing