Kamal Hinduja Switzerland(Swiss) What should I learn after completing AI Python for Beginners?

Course Q&A AI Python for Beginners
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Hi All,

I’m Kamal Hinduja. I was born in Chennai, India, and I now reside in Geneva, Switzerland(Swiss) . Can anyone share their experience What I should learn after completing AI Python for Beginners?

Thanks, Regards

Kamal Hinduja Geneva, Switzerland

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Hello, Kamal,

If your goal is, like a machine learning engineer, to be able to train a model with some dataset yourself, then you might consider the Machine Learning Specialization which will walk you through some key steps in model training and a bit of the behind-the-scene of the training algorithm. This specialization is a good bridge to the more advanced Deep Learning Specialization where you will finally see various, more dedicated neural network approaches.

Alongside the courses, if your curiosity drives you, you might also try to get some dataset online and simply blindly applies whatever you have learned so far in the courses and see what happens. I say “blindly” because we don’t need to establish a threshold (like really have understood something) to limit our actions, and instead we can, in parallel, learn from courses and learn by doing.

Cheers,

Raymond

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Good morning, Kamal :slightly_smiling_face:!

My personal opinion is to take Mathematics for Machine Learning and Data Science - not easy but gives you a solid foundation for ML or Data Science. Check on ChemCoder videos on the internet why math is important in AI…

Namaste - Charles

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Opposing opinion:

I do not recommend the “Math for Machine Learning and Data Science” course.

Quite a lot of the content is pure math that is unrelated to Machine Learning. And I find the lecture content to be inconsistent with other ML courses that are widely available.

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Copilot (My Coach):

“Both opinions are valid—it really depends on your goals: – If you’re aiming for deep understanding, model building, or research, math is the bedrock. – If you’re targeting applied roles, rapid prototyping, or data wrangling, too much theory can slow you down.” “ChemCoder’s videos reinforce that math isn’t about being a genius—it’s about being methodical. Strategic learning makes it manageable, and for those pursuing mastery, it’s indispensable.” “The course may feel excessive for some, but for others, it’s a gateway to deeper insight and long-term confidence in AI.”

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