Career Prospects After a Course on Machine Learning

Data Engineer/Data Architect:

Data engineers have a completely different job role than ML engineers. As a Data Engineer, you’ll be responsible for working with an organization’s wholesome ecosystem. You’re recommended to have a working knowledge of Hadoop, MapReduce, Hive, MySQL, MongoDB, and Data Streaming. If you have a good knowledge of programming, you already have an added advantage in the job. In addition, you should be proficient in R, Ruby, Python, C++, Perl, and more.

If you work as a Data infrastructure engineer, you’ll be working with developing, constructing, testing, and maintaining highly scalable data management systems. You’ll develop custom applications that can perform analytics on heaps of data. You’ll also be responsible for collecting and storing data, doing real-time processing, and using it all to analyze the data via an API.

Data Scientist:

This is easily one of the most in-demand job professions in the tech. world today. Data scientists are, ideally, experts in languages like Python, R, SAS, MatLab, Hive, Pig, and more.

Being proficient in such Big Data technologies and analytical tools is a prerequisite for the job role. Simply because as a Data Scientist, you’ll be sifting through large amounts of unstructured data in order to derive insights and help come up with better future strategies. Other than that, you’ll also be required to clean, manage, and structure large chunks of data from disparate sources. This, too, requires the usage of sophisticated Big Data tools and technologies.

Data Analyst:

Data Analysts are persistent and passionate data miners who have a strong background in statistics, mathematics, and the basics of coding. The companies expect a data analyst to be familiar with data storing and retrieval systems, data visualization, Hadoop-based analytics, ETL tools for data warehousing, and other business intelligence concepts. The core responsibilities of a Data Analyst include designing, deploying, and maintaining algorithms, culling information and recognizing risks, extrapolating data using data modeling techniques, and pruning data.

Also Read, clustering in machine learning

The Future of Machine Learning

What we talked about are just the paths to get you started. And once you’re on it, there’ll just be growth, for the future of Machine Learning is extremely promising. There is, already, an urgent need for professionals who are not only trained well in Machine Learning but are also well-versed with the most important tools, techniques, and technologies. If you want to be one of those professionals, prepare yourself by diving deeper into machine learning and getting your hands dirty. That is the only way you’ll get deeper into what you learn and be able to prepare yourself for the future that lies.

Whether you’re a programmer, a maths graduate, or even a bachelor of Computer Science, you can land yourself any of these jobs with the relevant skills and knowledge.

Conclusion

These are the most sought-after jobs once you’ve successfully completed a course on Machine Learning and feel that you’re ready to face the job market. Reading through the article would’ve helped you narrow down the field of your interest. Once you’re there — dive deeper into precisely what does that job role entail, and get going! You can also consider our online coding courses such as the Data Science Course to give your career an edge over others.