Machine learning specialization course - advice for learning Python

Course Q&A Machine Learning Specialization MLS Resources
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Hi everyone,

I hope you’re doing well! I’m reaching out for some advice on how to improve my Python programming skills, and I would greatly appreciate any help or guidance you can offer.

A bit about my background: I hold a degree in Actuarial Science and have many years of experience working in the insurance industry. A few months ago, I decided to embark on my journey into Machine Learning (ML). To prepare, I started by studying some Python basics (e.g., variables, lists, and similar concepts) before diving into the Machine Learning Specialization course.

I recently completed the course and feel that I have a reasonable understanding of the theoretical concepts. I was also able to complete the assignments without major issues. However, I struggled to understand around 90% of the Python code in the optional labs and assignments, particularly when it came to working with Python libraries.

Now, I’m eager to start working on projects related to what I learned in the course, but I feel unprepared due to my limited Python programming skills. I’ve seen some advice on this topic in previous discussions, but I was wondering if anyone could share specific recommendations or resources—especially free tutorials—to help me improve my Python skills and better prepare for ML projects.

Thank you in advance for your time and support!

Best regards,
Emiliano

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Tip;
If you want to learn Python coding, avoid attending any course that has “AI” or “ML” in the title. Those will rely on chatbots to give you programming advice. That doesn’t really help with fundamental coding skills.

Free tutorial method 1:
A very popular video sharing site (whose initials are YT) has a lot of good Python tutorials. You can pick one based on the number of views it has registered.

Free tutorial method 2:
python.org has its own tutorials. Go to the Docs section, then click on Tutorial.

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Hi TMosh.
Thanks for your help.
I’m starting today with the challenge of reviewing lab codes with more detail, before moving forward.

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Good luck, Emiliano :wink:

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