Practical prompt engineering techniques to maximize the capabilities of Large Language Models (LLMs)
Series Overview
This series is a comprehensive 5-chapter educational content covering Prompt Engineering from basics to practical applications.
To effectively utilize Large Language Models (LLMs) like ChatGPT, Claude, and Gemini, proper prompt (instruction) design is essential. This series teaches systematic techniques for eliciting high-quality responses from LLMs with abundant practical examples.
Features:
- ✅ Practice-Oriented: Over 50 working prompt examples
- ✅ Systematic Structure: Basics → Techniques → Applications → Advanced Skills → Practical Projects
- ✅ Diverse Use Cases: Applications in business, education, research, and development
- ✅ Ready to Use: Copy-and-paste templates for immediate implementation
- ✅ Latest Techniques: Chain of Thought, Few-shot Learning, Role Prompting, and more
Total Study Time: 100-125 minutes (including prompt execution and exercises)
Learning Objectives
Upon completing this series, you will acquire the following skills:
- 🎯 Effective Prompt Design: Create clear and specific instructions
- 🎯 Advanced Technique Utilization: Distinguish and apply Zero-shot, Few-shot, and Chain of Thought
- 🎯 Task-Specific Optimization: Design prompts tailored to summarization, translation, analysis, code generation, etc.
- 🎯 Quality Improvement Techniques: Systematically enhance LLM output quality
- 🎯 Practical Application: Apply techniques in real business and research scenarios
How to Study
Recommended Learning Path
🎯 Complete Mastery Course (All Chapters Recommended)
Target: Those who want to systematically learn prompt engineering
Approach: Chapter 1 → Chapter 2 → Chapter 3 → Chapter 4 → Chapter 5
Duration: 100-125 minutes
Outcome: Comprehensive mastery from basics to applications, ready for immediate practical use
⚡ Fast Track Course (For Experienced Users)
Target: Those with LLM experience who want to deepen their skills
Approach: Chapter 1 (review) → Chapter 3 (applications) → Chapter 4 (advanced)
Duration: 60-75 minutes
Outcome: Master advanced techniques, significantly improve prompt quality
🔍 Targeted Learning
Target: Those who want to learn specific topics
- Basics Only: Chapter 1 (20-25 minutes)
- Chain of Thought: Chapter 1 → Chapter 3 (45-50 minutes)
- Practical Application: Chapter 5 (20-25 minutes)
Chapter Details
Chapter 1: Fundamentals of Prompt Engineering
Learning Content
- What is Prompt Engineering
- Six characteristics of good prompts
- Zero-shot and Few-shot learning
- Chain of Thought (CoT) prompting
- Practical prompt templates
- Common failure patterns and improvements
Chapter 2: Basic Prompt TechniquesComing Soon
Planned Content
- Role Prompting
- Context Setting
- Output Format Specification
- Constraint Setting
- Task Decomposition
- Prompt Template Library
Chapter 3: Applied Prompt TechniquesComing Soon
Planned Content
- Tree of Thought
- Self-Consistency
- ReAct (Reasoning + Action) Pattern
- Multi-turn Conversation Design
- Prompt Chain Construction
- Error Handling and Quality Management
Chapter 4: Task-Specific OptimizationComing Soon
Planned Content
- Text Summarization Optimization
- Translation Quality Improvement
- Code Generation and Review
- Data Analysis and Extraction
- Creative Content Generation
- Question-Answering System Development
Chapter 5: Practical ProjectsComing Soon
Planned Content
- Business Document Automation
- Research Paper Summarization System
- Customer Support Bot
- Educational Content Generation
- Prompt Library Development
- Continuous Improvement and Best Practices
Overall Learning Outcomes
Upon completing this series, you will acquire the following skills and knowledge:
Knowledge Level (Understanding)
- ✅ Understand fundamental principles of prompt engineering
- ✅ Explain differences between Zero-shot, Few-shot, and Chain of Thought
- ✅ Understand characteristics of effective prompts
- ✅ Know task-specific optimization methods
- ✅ Understand LLM limitations and countermeasures
Practical Skills (Doing)
- ✅ Create clear and specific prompts
- ✅ Design appropriate examples (Few-shot)
- ✅ Guide step-by-step reasoning with Chain of Thought
- ✅ Optimize prompts according to tasks
- ✅ Evaluate and improve prompt quality
Application Ability (Applying)
- ✅ Solve business challenges with prompts
- ✅ Apply prompt techniques to new use cases
- ✅ Build and manage prompt libraries
- ✅ Share prompt best practices within teams
Prerequisites
Required Skills
- 💻 Experience using ChatGPT, Claude, Gemini, etc. (able to ask basic questions)
- 💻 Ability to read and write in English or Japanese
Recommended Skills (Beneficial)
- 📚 Basic knowledge of machine learning ("Introduction to Machine Learning" series recommended)
- 📚 Fundamental understanding of natural language processing
Frequently Asked Questions (FAQ)
Q1: I've only used ChatGPT a little. Will I be okay?
A: Yes. If you have experience asking basic questions, that's sufficient. This series teaches systematically from the basics.
Q2: Which LLM should I use?
A: You can learn with any of ChatGPT (GPT-3.5/4), Claude, or Gemini. Most techniques are universally applicable. Free plans are sufficient for learning.
Q3: Is programming knowledge required?
A: Not for Chapters 1-3. Basic programming knowledge enhances understanding in Chapter 4 (code generation) and Chapter 5 (practical projects), but it's not mandatory.
Q4: How long does it take to complete?
A: All chapters total 100-125 minutes. At a pace of one chapter per day (20-25 minutes), you can complete it in about one week. Weekend-intensive study is also possible.
Q5: Can I apply this immediately in business?
A: Yes. Even just the basic techniques from Chapter 1 can be applied to daily tasks like email writing, document summarization, and brainstorming. Chapter 5 covers practical business use cases.
Q6: Can I copy and paste the prompts?
A: Yes. All prompt examples have been tested and can be used as-is. Customization for your specific needs is also recommended.
Let's Get Started!
Ready to begin? Start with Chapter 1 and step into the world of prompt engineering to maximize your LLM potential!
Update History
- 2025-12-01: v1.0 Initial release (Chapter 1 only)
Your LLM journey begins here!