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Skills Needed to get Machine Learning Jobs

The unquestionable reality of Machine Learning is its applicability in every aspect of our lives. Today, almost everything that we perform requires the usage of Machine Learning and it has hugely impacted many social fields such as finance, education, etc. In fact, there is not a single ground where Machine Learning cannot be applied to.
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 vehement demand for Machine Learning engineers and the openings for Machine Learning jobs.
The most crucial challenge involved in the profile of Machine Learning jobs involves solving the ‘complex’to ‘understandable solutions’. This is why there are a particular set of necessary skills that one must possess in order to secure formidable Machine Learning jobs. Here are some of the important skills one must have to get a machine learning job and to succeed as a machine learning engineer:

Essential Skills needed to get Machine Learning Jobs

Programming and fundamentals of Computer Science

Computer Science is an important skill that is necessary for a Machine Learning Engineer. 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 stand implementation of ML 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. Learn about the advantage and disadvantage 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 for Machine Learning job opportunities. 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.