AI Statistics for Non-Majors
arigaram
Without a single formula or line of code, this penetrates the essence of basic statistics necessary for AI development and application.
Beginner
AI
We introduce basic prompt patterns for coding and advanced API prompt patterns for leveraging artificial intelligence.
How to write prompts for development
Core development and documentation concepts, including Refactoring, TDD, BDD, Gherkin, and Cucumber.
The course is currently being finalized. Please note that there is a downside: you may have to wait a long time until the course is fully completed (although I will be adding supplementary materials frequently). Please take this into consideration before making your purchase decision.
March 20, 2026
Due to the rapid development of AI technology and the growing importance of agentic coding techniques, I have begun restructuring the entire course and re-producing all lectures from scratch. The course will be reorganized into approximately 70 lessons across 10 sections. The topics for each section are as follows, with sections 7, 8, 9, and 10 specifically focusing on agentic coding.
Section 1. Developers in the Era of Prompts
Section 2. Code Generation Patterns
Section 3. Refactoring Patterns
Section 4. Testing and Debugging Patterns
Section 5. Documentation and Transformation Patterns
Section 6. Style and Convention Patterns
Section 7. Introduction to Agentic Coding
Section 8. Project Context Setting Patterns
Section 9. Core Agentic Coding Patterns
Section 10. Agentic Coding Practical Workflow
Section 11. Prompt Chaining and Workflows
Section 12. Security and Quality Check Patterns
Section 13. Meta-Prompts and Automation
Section 14 (Appendix). Prompt Pattern Reference Card
I will delete the existing sections that are empty and keep the sections that contain at least some lesson content by tagging them as [1st Edition] until all the 2nd Edition sections are completed. Therefore, those who are already taking the course will be able to continue without interruption. I will then delete them after completing all 14 sections of the 2nd Edition.
January 23, 2026
I have released the table of contents for all lessons to be included in the professional section.
While revealing the full table of contents for the professional section, I changed the course title from "Prompt Patterns (Vibe Coding) for Developers" to "Prompt Patterns for Developers" to make it more inclusive.
December 10, 2025
We have started posting the lesson content to be included in the Professional Section (Section 14 ~ Section 55).
November 30, 2025
We have categorized some of the sections within the advanced course as professional sections. We plan to add more specialized classes to these professional sections.
September 18, 2025
Added the precautions to the detailed introduction page.
August 22, 2025
The detailed lesson curriculum for the sections making up the advanced course has been set to private. These will be made public section by section as they are completed in the future.
In this course, we explore how to write better prompts by introducing prompt engineering techniques necessary to make the most of various AI coding tools such as GPT, Copilot, ChatGPT, Claude, and Cursor.
Developers who write prompts well are faster and more competent.
Developers are no longer just people who write code.
In a development environment collaborating with AI, 'what and how to request' has become a core competency.
We categorize prompt patterns by type and provide them along with practical examples.
You can check the code generated by the prompt.
News reports frequently suggest that companies are no longer hiring junior developers and are even letting go of existing ones due to artificial intelligence. Now is the time to transition from being a traditional programmer to a programmer who utilizes prompt patterns—a "Prompt Programmer."
Don't just use outdated development tools; actively utilize AI to significantly increase your productivity.
Developers who have programming experience but are unfamiliar with using AI
Developers who spend a lot of time on repetitive coding, refactoring, and documentation tasks
DevOps, data analysis, security, and those who want to expand into new areas using prompts thông qua câu lệnh (prompt)
Developers who can handle basic coding but lack habits for testing, refactoring, and documentation
Those who want to adapt quickly to practical work and grow into a “productive developer” through AI tools
Those who need to handle code writing + infrastructure management + collaboration alone or in a small team with limited resources
Startup developers who need rapid prototyping and iterative experimentation
People who are already using Pandas, NumPy, Matplotlib, etc., but want to strengthen data processing & visualization automation
Analysts interested in AI prompts → code automation → workflow optimization
Learners who want to quickly master new languages/frameworks
Summarizing technical papers → Reproducing code: Researchers who want to accelerate this process with the help of AI
People who want to understand the flow of prompt-based code review, quality control, and automation while collaborating with development teams
Those who want to streamline collaboration between planners, designers, and developers
Core Topics: Why prompts are important for developers, the changing work structure, and basic concepts.
Lessons covered: Importance, definition of a good prompt, factors to consider when writing, the value of patterns, etc.
Key Topic: Basic patterns for requesting actual functional code from AI.
Lessons covered: CRUD, UI components, state management, event handling, asynchronous, framework-based requests.
Core Topic: Requests for improving and structuring existing code.
Lessons covered: Improving readability, function extraction, removing duplication, OOP conversion, immutability, and performance improvement.
Core Topic: Ensuring quality through test automation.
Lessons covered: Unit/integration testing, exception cases, mock/stub, TDD style, coverage expansion.
Key Topics: Automation of comments, API documentation, README, and change history.
Lessons covered: Function comments, docstring, JSDoc/TSDoc, technical blogs, API documentation, and changelog summaries.
Core Topic: Automation of conversion between languages and frameworks.
Lessons covered: JS↔TS, Python 2↔3, Java↔Kotlin, jQuery↔React, REST↔GraphQL, SQL↔NoSQL.
Key Topic: Code interpretation and error detection through AI.
Classes covered: Code explanation, complex logic interpretation, complexity analysis, security issues, and debugging log automation.
Key Topic: Applying consistent code styles.
Lessons covered: ESLint, PEP8, Prettier, custom rules, semicolon/indentation conventions.
Core Theme: Project-based prompt utilization.
Lessons covered: Prompt chaining, iterative improvement strategies, and collaboration standardization.
Core Topic: Data Preprocessing, Analysis, and Visualization.
Classes covered: Pandas/Numpy preprocessing, visualization, efficient large-scale data processing, CSV/JSON/XML parsing, and log analysis automation.
Core Topic: Infrastructure code automation through AI.
Lessons covered: Dockerfile, Kubernetes manifests, CI/CD pipelines, Terraform/CDK, server configuration files.
Core Topic: Security vulnerabilities and quality assurance.
Lessons covered: Vulnerability scanning, static analysis, API key management, load testing, security log automation.
Core Topic: Combined use of image, voice, and documents.
Lessons covered: Image→Code, Voice Command→Code, Figma→UI Code, Document Summary+Code, Multimodal Workflow.
Core Theme: Managing and automating the prompts themselves.
Classes covered: Templatization, LangChain, Performance Benchmarking, Zapier/n8n, Tool-based Agents.
Core Topic: Team-level prompt utilization strategies.
Lessons covered: Code review automation, team convention-based prompts, Jira/Notion integration, history management, multi-disciplinary collaboration.
Core Topic: Prompts for self-study and research.
Lessons covered: Tutorial generation, open-source exploration, paper summary to code, algorithm learning, learning roadmap automation.
Core Topic: Utilization in the service operation stage.
Classes covered: Failure analysis, log-based error detection, performance monitoring, batch scripts, emergency patch code.
Core Topic: Improving User Experience.
Classes covered: Accessibility standards, multilingual i18n, user feedback integration, A/B testing code, UI animation.
Core Topic: Industry-specific customized prompts.
Classes covered: Game development, financial data, medical data protection, e-commerce, IoT/embedded.
Key Topic: Responsible AI Development.
Classes Covered: Personal information de-identification, data bias verification, copyright/license review, safe input handling, and ethical code review.
Prompt engineering skills that can boost coding productivity by 2 to 3 times
Prompt templates for automating repetitive tasks
A foundation for prompt standardization that can be shared with team members
Hands-on prompt experience that can be applied immediately to real-world projects
Future competitiveness as a “developer collaborating with AI”
You just need to prepare one of the AI-based coding tools such as ChatGPT, Gemini, Grok, Claude, or Copilot.
The lecture notes are attached as a PDF file.
Since the explanations use JavaScript and Python, it is helpful to have basic knowledge of these two languages.
It will be very helpful if you have a basic understanding of refactoring concepts. In this regard, my separate lecture, "Clean Coding: Easy Techniques for Writing Good Code Using Cooking Analogies," will also serve as a great reference.
Who is this course right for?
Those who want to develop faster and more accurately using AI tools
Those who want to use ChatGPT or Copilot effectively but feel lost on what to ask and how to ask it.
Those who want to automate repetitive development tasks using prompts
Developers who want to collect prompt examples that can be used immediately in practice.
A manager looking to introduce a culture of AI prompting to their team
Need to know before starting?
Python language
Refactoring
JavaScript language
692
Learners
38
Reviews
2
Answers
4.6
Rating
18
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I am someone for whom IT is both a hobby and a profession.
I have a diverse background in writing, translation, consulting, development, and lecturing.
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