I want to send this particular topic of conversation to the Codecademy Data Science Content Creator, but I still welcome other Codecademy moderators and learners in this conversation.
I am almost finished with my Data Science path. I am at the AI Minimax Algorithm module.
To be perfectly honest and blunt, I am not so sure why this particular module is being taught in the Data Science Course.
From finishing the Linear Regression Module, KNN Module, Random Forest Module, and Classification: Naive-Bayes module, and now jumping straight into this AI Minimax Algorithm module, I feel a disconnect in my learning. As a result, I have no idea what’s the main idea of this particular module.
Don’t get me wrong, I know how to play tic-toe, but what is the main reason this module is included in the Data Science curriculum?
Also, as I am completely new to the Machine Learning field, it has not been easy to understand the narratives you made in each module of Machine Learning (let’s just say the narratives made in these modules are not entirely beginner’s friendly, there is definitely a lot of room for improvement there) but I still do get what you are trying to convey. Except for this AI Minimax module.
So, can someone from the Codecademy reach out to me and answer my question? Because I don’t wanna put my time and energy into something that is not related to my main purpose of taking the data science curriculum in the first place.
I don’t mean to brag but I have been very disciplined with my learning here (check my profile for proof) and I just thought Codecademy should know if someone like me thinks this way, there must be others from the past (and potentially from the future) think of the same thing too.