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Skills Needed to get Machine Learning Jobs

One thing that is unquestionable about Machine Learning is its applicability in every aspect of our lives. Today, almost most jobs have some component of Machine Learning attached to it and it has hugely impacted many social fields such as finance, education, etc. In fact, there are very few fields where Machine Learning Jobs are not available.

It is only natural to want to join the winning team with the world going ahead technologically at a very rapid speed. This brings to light the increasing demand for Machine Learning engineers and the openings for Machine Learning jobs.

The most crucial challenge involved in Machine Learning jobs involves solving the ‘complex’ problems by coming up with ‘understandable solutions’. This is the major non-technical skill that one must possess if they wish to apply for Machine Learning Jobs. Here are some of the important non-technical skills that can propel one towards machine learning jobs and help them succeed as a machine learning engineer:

Essential Skills needed to get Machine Learning Jobs

These are a few important skills that are required to get Machine Learning Jobs. Most of them are quite technical in nature. This does not mean that Machine Learning Jobs are only available for people from a technical background. With the amount of material available on the internet today, anybody with zeal to learn will be able to learn the basics which can help them acquire at least a few of the essential skills required in Machine Learning Jobs.

Programming and fundamentals of Computer Science

Computer Science is an important skill that is necessary for all Machine Learning Jobs. In fact, Computer Science isn’t limited to Machine Learning engineers alone. Every programmer must be equipped with computer science knowledge. The important fundamentals of computer science include-

  • Data structures- stacks, queues, multi-dimensionalarrays, trees, graphs, etc.
  • Computability and complexity- P vs. NP, NP-complete problems, big-O notation, approximate algorithms, etc.
  • Algorithms -searching, sorting, optimization, dynamic programming, etc.
  • Computer architecture- memory, cache, bandwidth, deadlocks, distributed processing, etc.

The algorithms and libraries of Machine Learning

Machine learning algorithms are a very essential requirement for machine learning jobs. The standard implementation of Machine Learning algorithms can be availed from libraries/packages/APIs such as TensorFlow, Theano, etc. These algorithms must be applied with a model that is most suitable. It is possible to learn about the advantage and disadvantages of the approaches by practicing on platforms like Kaggle, Tunedit, HackerRank, etc.

Probability and Statistics

The probability and techniques of Machine Learning derived from algorithms like Markov Decision Processes, Hidden Markov Models, Bayes Nets, etc., is a skill one must possess/enhance to pursue Machine Learning jobs. Statistics and analysis methods like ANOVA, hypothesis testing, etc., are also an extremely important part of ML probability and statistics.

Software and System Design

Software and system designing is essential for organizing the program modules for changes, development, and forming programs. Hence, having a strong grasp in software engineering and system design is one crucial skill to land attractive Machine Learning jobs. Documentation, system design, modularity, etc., are some of the software and system design practices one must be familiar with.