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Ashish Bansal
I am a self-taught machine learning engineer. I have found incredible value in MOOCs. I have taken most of my courses on Coursera and a couple from Udemy. Coursera and Udemy courses were more focussed on application with just enough theory. I found that my job was more towards application than to discover new algorithms. In that context, I felt the MOOCs provided a lot of value as I could accelerate applications of machine learning to shore up my knowledge.
There is a serious lack of decent machine learning talent in the industry. Universities cannot produce enough people to fill the demand. See this article on jobs. I have found that people from industry that retool themselves in machine learning are quite valuable. When I hire for my team, a Ph. D. does rate high, however, I never reject candidates because all they did was a MOOC. One of the areas where Ph. Ds are pretty bad is in data preparation. In most academic research, data is ready to consume. They have clean data sets that they work on. In real life, 60-80% of the job is dealing with messy data which people with more real world experience are better at.
The nano-degree has some powerful content. Dont take it for the 'nano-degree' title. Take it for learning and applying and becoming better. You should consider the courses in Coursera as alternatives as well. Showcase your knowledge by writing articles, tutorials or Kaggle competitions. Jobs will happen.
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I am a self-taught machine learning engineer. I have found incredible value in MOOCs. I have taken most of my courses on Coursera and a couple from Udemy. Coursera and Udemy courses were more focussed on application with just enough theory. I found that my job was more towards application than to discover new algorithms. In that context, I felt the MOOCs provided a lot of value as I could accelerate applications of machine learning to shore up my knowledge.
There is a serious lack of decent machine learning talent in the industry. Universities cannot produce enough people to fill the demand. See this article on jobs. I have found that people from industry that retool themselves in machine learning are quite valuable. When I hire for my team, a Ph. D. does rate high, however, I never reject candidates because all they did was a MOOC. One of the areas where Ph. Ds are pretty bad is in data preparation. In most academic research, data is ready to consume. They have clean data sets that they work on. In real life, 60-80% of the job is dealing with messy data which people with more real world experience are better at.
The nano-degree has some powerful content. Dont take it for the 'nano-degree' title. Take it for learning and applying and becoming better. You should consider the courses in Coursera as alternatives as well. Showcase your knowledge by writing articles, tutorials or Kaggle competitions. Jobs will happen.
See Questions On Quora
Continue reading...
