I have been a good programmer most of my career and also a good manager. Done cloud computing, big data, C and Java etc.
Sharp increase in the stability of cloud computing seems a bit scary to me as the same has increased profoundly in the last 5 years.
Azure/GCP now sell a lot of big data products as commodities!
To keep up with the tide, does it make sense to do an MS in ML/AI at this point from a reputed university? I do not want to start as a fresher in this domain but am also afraid that zero experience in this field will go against me even if I do MS now.
Also, most ML/AI engineers seem unhappy as they complain about data cleaning and generating test data for model training which is much less interesting than actual algorithms of ML/AI.
#machinelearning #ai #cloud #bigdata
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Much like CS in general, what you learn in a few years of school for ML pales in comparison to what you learn working on production ML systems.
ML engineering is hard, but rewarding, cutting edge, and if you are good, pays bank.
- 15+ YOE ML Engineer with a good chunk of that hiring data scientists and ML engineers