[Todai GCI 2nd Session] Completed the assignment in 1 hour and 25 minutes! Prompts for beginners to turn AI into the 'ultimate private tutor' [2026 Summer]

I tried solving the 2nd GCI assignment.
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1. Introduction: The 2nd assignment is 'Python Basics'

The theme of the 2nd session is the gateway to programming: Python basics. I've kept a record of the points where I thought, 'Oops, that was close,' as a memo for myself.
• The trap of full-width vs. half-width characters: In programming, 'half-width' is the absolute rule. Even a single full-width '=' or '>' will immediately make the computer grumpy.
• The law of indentation: In Python, spaces are not just empty gaps but the 'structure' itself. They are the boundary lines that separate the 'inside' and 'outside' of a function.
• Where 'return' belongs: I tried to use 'return' outside of a function and got scolded with an 'outside function' error. Magic can only be used 'inside the box' (the function).
• The direction of assignment: A = B is not a command meaning 'A equals B,' but rather 'put B into A.' If you get this direction wrong, the calculation will proceed with empty variables.

2. Why I was able to clear it in 1 hour and 25 minutes | The moment past 'experience' connected the dots

The reason I was able to clear it in 1 hour and 25 minutes this time might be because I still had faint remnants of past experience.

• New graduate training at a systems company: I wasn't writing code actively in practice, but I had experience copying C language code through self-study and studying for basic information technology exams.
• 7-8 years of R experience: I used it for receipt analysis at my second job, but I remember having no confidence and barely getting it to work by asking my supervisor.

I was practically a beginner, but I think the reason I felt 'Oh, I can actually do this!' when touching Python this time was because those 'thin memories' served as a foundation.

3. A message to beginners: At first, just grasping the 'big picture' is enough

Even now, I don't clearly understand everything. There are many parts where I'm just proceeding based on a 'vague sense of the atmosphere.'
But I think that's fine when starting something new.
'Even if you feel like you're in a fog at first, if you keep going, the resolution will gradually improve.'
As a beginner, the trick to not getting discouraged might be to not try to understand 100% from the start, but to first aim to grasp the big picture and accumulate the feeling of 'Oh, it worked!'

4. How to get along well with AI | Growth stops if you just get the 'answers'

In GCI, the use of AI is encouraged, but how you use it is important. I don't ask AI for the 'answers themselves.'

By treating AI as a 'private tutor that gives hints' rather than an 'answer key' in this way, the level of understanding when you finally reach the correct answer increases significantly.

5. The 'solve from the assignment' preparation style

Actually, I tried solving this assignment as 'preparation' before listening to today's afternoon lecture.
It's the same with medical school studies, but I feel that the flipped learning style of trying to solve problems first to clarify my own 'unknown areas' leads to the best retention.
After this, I'm looking forward to watching the main lecture again and enjoying checking my answers to see 'if there is a gap between my understanding and the instructor's explanation' and 'if there is a smarter way to write it!'

6. Conclusion: Towards the next assignment

With the 2nd session, I've made a good start with the cycle of preparation -> practice -> lecture.
While using the 'savings' of my past experience (basic information technology and R), I am overwriting it with a new sense of Python. This process is surprisingly comfortable.
The next homework will surely not be straightforward either, but I will climb the stairs to becoming a data scientist one step at a time, looking forward to this co-creation with my 'AI tutor' and the excitement of 'checking my answers.'