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Are Mechanical Engineers, skilled enough for Data Science Stream?


Business Toys - Learning paths for Data Science aspirants

In all other fields, mechanical engineers are excellent nowadays. There is no exception to analytics. Let me tell you that mechanical engineering is considerably easier. If you know gear law, fluid physics and so on, learning to play data is not a science of cockets. In truth, it is easier to do things, it needs only two traits, analysis and logic.Data Science is a great field for Math and Stat enthusiasts.But, being a Mechanical Engineer you have to carefully pave your way to become a Data Scientist.

Switching from mechanical background to the one with data is definitely not easy but still doable. Anybody looking for the transition, should for sure check these boxes -

  • 1) Look into the maths of the different models for data science start from linear regression and build on top of it
  • 2) Start analyzing datasets, there is no better experience than data mining and learning from there. Use python pandas or any other toolkit you might like
  • 3) Create a portfolio of personal projects that are creative and interesting. Nothing more powerful than showing a potential employer your creativity. Be careful to not copy paste reimplementation of open source projects in your CV, it looks very bad.
  • 4) Connect with other people and discuss experiences, books, tutorials etc

There are other areas you can work on yourselves at -

  • 1) Choose the courses wisely to upskill yourself.
  • 2) Do some online certifications to gain more relevant knowledge and hands on experience on the relevant tools
  • 3) Participate in data competitions which would attest your knowledge.
  • 4) Do some cool and live industrial projects!

Once done with these, you would hardly require placement assistance. Self browsing on the internet, from linkedin and applications via several job portals will get you through. Also, having friends around in the field, would pay off with referrals for relevant openings at their organizations. Secondly, go through enough interview tutorials, to get accustomed to the type of questions you might expect in yours.

While applying to different openings, some things to keep in mind -

  • 1) Your resume should be honest enough and most updated
  • 2) Try aligning your projects and put them on in the resume using an ample number of keywords.
  • 3) Don’t apply at places where JD strictly mentions the required experience, for it will give nothing but despair.

Data Science is not just one topic but is composed of so many small ones. The science per se where one can discover new algos. The engineering where one creates and deploys scalable infrastructures that solve business problems. The visualisation where one mines data to create meaningful visualizations for insights. The one who is awesome at all the above is a unicorn. Irrespective of what domain you belong to, be it engineering specialized in Mechanical, or be it a simple graduate in Arts, you can specialize in any with what suits the best to your aptitudes and passion and excel the same.

After getting through the few obstacles in the way, you are born to be a Data Scientist. Choose wisely and believe in yourself and your gut. All the very best for upcoming ventures.


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