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In my PhD, I will work with ML models. However, I will only use ready-made models as a tool, but I want to delve deeper into Artificial Intelligence not just to use ready-made models, but to understand how it works and create my own AI.

I noticed that most of the content I found talked more about how to use ready-made tools. I am interested in, over time, being the person who 'makes the medicine' and not just the one who 'takes it'.

I was considering doing another degree in Computer Science, but I was hesitant. Doing another degree to learn about AI at the same time as my PhD, I was thinking about using this time I will have during my postgraduate studies to study independently.

I found this free degree in CS, I took a look at the schedule and I don't know if everything is necessary to have this level of knowledge in AI.

Because, at least in Chemistry, many subjects are unnecessary to learn some topics.

Could you help me with what subjects I should take?

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  • $\begingroup$ Which topics do you think would be relevant, math, algorithms? Which subjects do you think suit this? What is your background knowledge? Do you have appropriate familiarity with basic concepts? i.e. what is overfitting: learning from noise, which for instance enable you to think of replacing dense with conv, instead of simply tuning hyperparameters. Do you understand AI research papers? Do you have smaller serious AI research efforts before joining Ph.D? $\endgroup$
    – Kenneth Kho
    Commented Jan 12 at 15:55

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A course in multivariable calculus is useful for understanding back-propagation.

Some familiarity with a programming language like Python would helpful to understanding how it all works, and for actually running some common libraries.

A course in statistics would be useful as well!

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