...
Python and SQL exercises. It’s ok to write some boilerplate code to solve your problem when you are working with data, but the purpose of code exercises is to learn how to code. It's an illusion that with the emergence of ChatGPT, this skill has become unnecessary: in order to create good prompts and debug the code written by ChatGPT, you need to be a good coder yourself!
If you didn’t write the code yourself, you will probably struggle to find flaws/bugs/gaps in it.
Ask it a question without thinking on your own, especially when learning new topics. To really understand the topic, you need to try to solve the problem yourself, this is how active learning works. Of course, it is often worth using ChatGPT, especially if you know what you're doing and don't want to waste time. But when you are just studying a topic, start solving problems yourself, and only then ask ChatGPT for guidance.
Solving tests at the end of the parts. The point of these tests is to consolidate your neural connections and test yourself. Of course, you can ask ChatGPT for explanations, but only after you have passed the test.
Remember: these tests are for self-assessment, and their score is not used for anything other than to help you reflect on your learning. Using any tools for these tests only gives you a false sense of progress.
Important:
Turing College encourages the responsible use of AI tools, recognizing their potential to enhance learning when used appropriately. We advocate for a balanced approach where these tools serve as complements to active learning and critical thinking. The misuse of AI tools, such as substituting personal effort completely with AI-generated solutions in projects is considered a breach of academic integrity. Such actions not only hinder personal growth but also compromise the values of honesty and integrity.
Prompts engineering: tips and good practices
...