Advice : Next steps in ML learning path for AEC industry

Hello everyone,

I hope this message finds you well. I’m reaching out to this forum seeking some guidance and recommendations regarding my journey in machine learning.

To provide some context, I have completed the following courses:

Python for Everybody Specialization (Coursera)
Mathematics for Machine Learning (Imperial College of London)
Machine Learning Specialization (Coursera)
Deep Learning Specialization (Coursera)
Data Science for Construction, Architecture and Engineering(edX)

These courses have laid a strong foundation for my understanding of the fundamentals in machine learning.

A bit about my professional background: I have over 15 years of experience in the AEC industry (architecture, engineering, construction), predominantly in BIM environments. As I look ahead to incorporating machine learning into my skill set, my aim is to harness AI solutions within the AEC sector.

Now, I am seeking advice on what steps to take next. Given this background, could you kindly recommend what courses or practical approaches I should consider? I’m particularly interested in a more hands-on approach, where I can apply my learning directly to real-world scenarios.

I greatly appreciate any insights or recommendations you can provide. Thank you in advance for your time and assistance.

Carlos.

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Consider within your own industry, if there are any situations where there is a lot of data available, but it isn’t being used to the best advantage.

TMosh,

Carlos’s question is really good. TMosh, would you mind expanding on your answer? Would you recommend, for example, doing a “side project” at work, if none is being requested? Or would it be more fruitful on average to get publicly available data, create a project from the data, then publish somewhere?

thank you,

Katherine

Yes.

Yes, this also. Though “publish somewhere” isn’t really a major factor unless you’re trying to get an academic job.

The key is to gain experience, and grab whatever opportunities present themselves along the way.

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