Copilot for Beginner Level Programmer??

[Prathamb6]

🏷️ Discussion Type

Question

💬 Feature/Topic Area

Copilot in GitHub

Body

As a beginner-level programmer... would you suggest Copilot or any other AI tools?... If yes, then which ones? I am planning to start learning Python and would build some apps one day.

[LixdyDev]

@Prathamb6 Hey! Honestly, if you are just starting to learn Python, I'd recommend holding off on Copilot for a bit.

When you are first learning, it is super important to write the code yourself to build muscle memory and understand the basic logic. If an AI auto-completes everything for you, it gets really hard to figure out how to fix your own bugs later on.

Instead of using a code-completion tool like Copilot, try using standard ChatGPT or Gemini like a personal tutor. Ask it to explain concepts or tell you why an error is happening, but make sure you write the actual code yourself.

Good luck with your apps!

[Prathamb6]

Thanks, I was thinking that too... I only asked this question to determine whether I would miss out on something by not using AI tools

[JoaoArnaud]

Yes, I would recommend using AI tools while learning Python, but I would use them as learning assistants rather than letting them build everything for you.

A simple setup would be:

• GitHub Copilot for code suggestions while you are programming.
• A conversational AI tool, such as ChatGPT, for explanations, debugging help, exercises, and code reviews.
• The Python documentation and a structured beginner course for learning the fundamentals.

You probably do not need several coding assistants at the same time. Start with one editor, one AI assistant, and one learning resource so that the tools do not become a distraction.

The most important part is how you use AI. Good requests include:

• “Explain this error and help me find the cause.”
• “Give me a hint without writing the complete solution.”
• “Review my code and point out what I could improve.”
• “Create an exercise about loops and functions.”
• “Explain this code line by line.”
• “Show me how to test this function.”

I would avoid asking AI to generate an entire application before you understand variables, conditions, loops, functions, data structures, modules, exceptions, and basic object-oriented programming.

A useful personal rule is: do not keep code that you cannot explain. AI-generated code may look correct while containing logical, security, or performance problems, so always run it, test it, and question the decisions it made.

For your first Python projects, you could build a calculator, a command-line to-do list, a file organizer, a small expense tracker, and later a simple web API. Try implementing each feature yourself first, then use AI when you get stuck or want feedback.

Used this way, Copilot can help you learn faster. Used only to copy complete solutions, it may make you productive temporarily while slowing down your actual understanding.

[manujayagunathilaka]

Yes, AI tools can be useful while learning Python, but I would treat them as a tutor rather than a replacement for practising.

For a beginner, I would suggest:

• Use GitHub Copilot for small code suggestions and repetitive code.
• Use an AI assistant to explain errors, review your code, and create practice exercises.
• Keep the official Python documentation and a structured beginner course as your main learning resources.

A good workflow is:

1. Try to solve the problem yourself first.
2. When you get stuck, ask for a hint rather than the complete solution.
3. Compare the suggestion with your own code.
4. Run and test the code.
5. Make sure you can explain every line before keeping it.

For example, instead of asking:

Build a complete calculator application for me.

Ask:

I have written this calculator function. Can you explain why it fails and give me a hint without rewriting the whole solution?

Also, avoid installing several AI coding tools at the beginning. One editor, one assistant, and one learning resource are enough.

GitHub Copilot can help, but the fundamentals should come first: variables, conditions, loops, functions, collections, exceptions, modules, and basic object-oriented programming.

A useful rule is: do not keep code that you cannot explain.

[Mr-Nilarnab]

I think the best approach is to change how you use AI as your skills grow, rather than deciding whether to use it or not.

For example:

Weeks 1–4: Avoid code generation. Use AI to explain concepts, error messages, and Python syntax.
Months 2–3: Let AI review your code, suggest improvements, and point out edge cases, but write the implementation yourself.
After you're comfortable with the basics: Start using GitHub Copilot for boilerplate code, repetitive tasks, documentation, and test generation, while continuing to implement the core logic on your own.

One habit that helped me is trying to predict what the code should look like before accepting an AI suggestion. If the suggestion matches your reasoning, great. If it doesn't, ask why before accepting it.

AI is most valuable when it shortens the time spent searching for information—not when it replaces the thinking process. If you can explain every line of code you keep, you're using it in a way that supports learning rather than replacing it.