Can AI Replace Your Coding Course?

With the rise of AI, the way we learn to code is rapidly changing. In a recent social media post, I reflected on how AI subscription services are making traditional coding courses less necessary. Why pay for a course when you can ask AI to generate a personalized curriculum for you?

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The Shift from Traditional Courses to AI-Driven Learning

In the past, learning to code often meant enrolling in expensive courses, following a rigid syllabus, and waiting for feedback from instructors. Now, with AI, you can have a dynamic, interactive, and personalized learning experience—right from your own terminal or editor.

The New Way to Learn: AI as Your Coding Mentor

Imagine asking an AI to create a step-by-step curriculum tailored to your learning goals. Each chapter or topic can be explained, discussed, and clarified until you fully understand. If you get stuck, you can ask the AI for further explanation or examples—no need to wait for a human instructor.

Example: Generating a Curriculum with AI

Suppose you want to learn Python web development. You could ask the AI:

“Please create a curriculum for learning Python web development from scratch.”

The AI might respond with a list of topics:

1. Introduction to Python
2. Python Syntax and Data Structures
3. Object-Oriented Programming in Python
4. Introduction to Web Development
5. Using Flask or Django
6. Building and Deploying a Web App

For each topic, you can request explanations, code samples, and even mini-projects. If you get stuck, you can ask for clarification or alternative explanations until you understand.

Terminal-Based AI: Learning in Your Own Workspace

Taking it a step further, using a terminal-based AI allows you to generate and store your curriculum in markdown files. Each topic gets its own .md file, where you can also document your questions and the AI’s explanations. This creates a living, interactive knowledge base that grows with your learning journey.

Example Workflow

1. Ask AI to generate a curriculum and save it as curriculum.md.

2. For each topic, create a new markdown file (e.g., 01-intro-to-python.md).

3. Write direct explanations and insights from your discussion with AI in each file. For example, after discussing “Introduction to Python” with AI, you can summarize the explanation, key points, and code examples you learned in 01-intro-to-python.md

4. Iterate and expand: As you learn, keep adding questions, code snippets, and notes. This way, your knowledge base grows organically.

The Pitfall: Hallucinations and Confusion

However, there is a caveat. Many learners jump straight into coding with AI assistance, only to find themselves confused. Sometimes, the AI’s explanations can be inaccurate or “hallucinated,” leaving users unsure about what they’ve just learned. It’s important to verify AI-generated content and seek clarification when needed.

Example of a Hallucination

Suppose the AI suggests a Python function that doesn’t actually exist, like str.reverse(). If you try it and get an error, this is a sign to double-check the documentation or ask the AI for clarification. Always test code and seek trusted sources when in doubt.

Tips for Effective AI-Assisted Learning

• Be proactive: Ask questions, request examples, and challenge the AI if something is unclear.
• Document everything: Use markdown files to keep track of your learning journey.
• Verify information: Test code, check official docs, and don’t hesitate to ask for clarification.
• Iterate: Learning is a process—keep refining your notes and understanding.

Conclusion

AI is transforming how we approach coding education. By leveraging AI to create and discuss personalized curriculums, we can learn more efficiently—but we must remain critical and engaged to avoid confusion. The future of learning is interactive, personalized, and, with the right approach, more accessible than ever.