Every industry is driven by data in today’s evolving technological world. Data Science, an interdisciplinary field that utilizes logical and analytical techniques, procedures, calculations, and frameworks, to extract information and insights from numerous types of data, has become a basic necessity for all businesses. In this article, let us, deep-dive, into how data science for mechanical engineers has been effective in driving good results.
Today, Data Science offers one of the most lucrative career opportunities in any industry. As the demand for Data Scientists is increasing, many professionals from different sectors are growing curious to know more about career shift opportunities.
We’ve had several learners and professionals from different academic backgrounds reach out to us in the past, asking us how difficult it is to make a shift to the Data Science domain. Out of these, learners and professionals who’ve pursued a degree in Engineering, especially Mechanical Engineering, also have shown a similar desire to make a successful career in the Data Science and Analytics domain.
While each student’s experience is different, we can safely say that keeping the academic background in engineering as a base, learners, as well as professionals who make a shift to the Data Science field, receive ample opportunities for career growth.
In this article, we shall discuss how to build a career in Data Science for Mechanical Engineers
The demand for Data Science professionals is at a record-breaking height at present. LinkedIn’s 2020 Emerging Jobs Report says that the Data Science domain is expected to see an increase in employment opportunities, along with Artificial Intelligence. If you are thinking of switching from Mechanical Engineering to Data Science, now is the right time.
Once you become a complete Data Science professional, you may join any sector. IT, FinTech, e-Commerce, Healthcare, Agriculture, Retail, Travel & Hospitality, Banking & Insurance; Data Science professionals are required across all industries and domains. They also receive a very handsome remuneration. According to PayScale, a Data science professional with 1-4 years of experience annually earns INR 5-7 lakh, and with 5-9 years of experience, one can earn an average of INR 13-14 lakhs per year.
If you are looking for upskilling opportunities in Data Science, there are several modes of learning available for both fresh graduates and professionals. You can take the help of online learning, work on open-source projects, read blogs, or follow fellow Data Science enthusiasts who showcase projects and work on real-world problems. You can also choose to enroll in an in-person classroom session, or an online curriculum, that involves live instructor-led learning.
While an in-person classroom session has its own benefits of real-time engagement and a wholesome learning environment, online training with live instructor-led sessions is also effective if you are not able to be physically present in a classroom. Just make sure whichever mode of learning you choose, the course you’ve selected for upskilling must be industry-relevant, must help you understand Data Science tools and concepts thoroughly, and help you become a Mechanical Engineer turned Data Scientist.
The most popular tools being used in the industry are MS Excel, Python or R, Hadoop, Spark, and Tableau. When it comes to programming for Data Science, Python is one of the most sought-after languages. Along with Python, R is also another popular programming language you must learn. R is a better tool for businesses because it is capable of making great business-ready reports using Rmarkdown (offers a framework for data science).
Once you gain more experience, you can use Shiny (a platform that allows users to interact with data sets and analysis) for interactive data products. When it comes to new tools, don’t be afraid to learn their usage and application for processing data.
Data science is an ever-evolving domain. This is a challenging field that empowers you with a mindset to drive decision-making and business responsibilities, with the help of data and insights. Data science requires perseverance and patience, however, it is also well worth the ride. While switching from Mechanical Engineering to Data Science, you must always be open to unlearn and start afresh. Don’t hesitate to try out new tools and experiment with your skills; this will help you stay relevant as per the emerging trends in the domain.
If you wish to join the league of successful Data Scientists, take a look at our “data science and machine learning course“, a placement guarantee program with Manipal Academy of Higher Education.