Machine learning is scaling up the charts in terms of popularity and career opportunities. Everywhere you look, engineering and non-engineering students are signing up for online courses and professional degrees that promise to make them fluent in this challenging yet deeply rewarding field.
And the hype is not there without reason. Machine learning is the field of teaching algorithms to make as accurate predictions and conclusions as are possible. As would be evident, this is a highly complex field. The demand for professionals is high and intense. And students are scrambling to fill it.
But it seems there are still endless and unending horizons in this field.
Machine learning in the cloud
The latest sensation in this field is machine learning in the cloud. It is concerned with taking machine learning capabilities up to the cloud and making them more easily available and accessible. As more and more organizations make use of ML and AI, they are bound to come up against certain problems, mainly:
- Knowledge gap, wherein the in-house team isn’t ML or data science proficient.
- Scalability. Using ML for small projects is easy. But the same cannot be said for larger ones and this extends to both hardware and software.
- Costs. As the size and scope of projects increases, more investment is needed for hardware and software to execute more complex algorithms.
The solution to all these problems comes with taking machine learning to the cloud.
- The knowledge gap is bridged because ML in the cloud doesn’t require very deep skills or hardcore knowledge
- Scalability becomes easy since the cloud is limitless in a sense and ample space is available for an everyday business to meet its requirements.
- Taking ML to the cloud is cost-efficient since it operates on a pay-per-use basis. Companies pay for what they use.
Machine learning in the cloud is, thus, the technology of the future. More and more companies will adopt it and choose it when they want to benefit from ML and AI capabilities. And when this happens, they will need professionals who can work well with ML and in the cloud as well.
In India, the salary for an ML engineer is already 3 LPA- 20 LPA. With the added skills of a cloud expert, the value of the position is predicted to go up considerably.
There you have it. The detailed lowdown on the career opportunities that are available in the field of ML right now. For the ones who are ready to take advantage of it and become the professional of today and tomorrow, upGrad brings to you the ML in Cloud program.
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