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Whether you agree or not, the hype for engineering is dying out real quick in the third decade of the 21st century. Although the trend for engineers was at its peak just five to eight years ago, technology is currently popularizing data science professionals over engineers. But this is not the end for people who did engineering in the first place. They still have an opportunity to make an amazing comeback with the help of data science. Yes, it is necessary for engineers to learn data science in 2021, in order to keep their place in the job market.
Data science is a blend of mathematics, machine learning, business decision tools, and algorithms. It helps businesses bring out knowledge and insight from structured and unstructured data. With data becoming the center of decision-making in almost every industry, the demand for data science professionals has also surged in the recent past. On the other hand, engineers are highly skilled professionals who need a switch. Most engineers are looking for ways to shift from their engineering jobs to data science or the big data industry to stay ahead in the job market. But adopting such a massive change involves challenges. As it is mandatory for engineers to learn data science to survive, they are willing to take the risk. Besides, the collaboration between engineering and data science is also bringing hope among many sectors including healthcare and pharmaceuticals, telecommunication, energy, automobile, banking, etc. They know how to enhance productivity and algorithm code quality by writing simple, performant, readable, and maintainable code. Engineers get to use engineering tactics along with business tools like Tableau, R, Apache Spark, SAS, Python, and many others.
As mentioned earlier, data science is a blend of many engineering necessities. Therefore, switching from engineering to data science involves expanding your skills in more data science-related tools. For example, if you are from Mechanical Engineering, then you must have a strong background in mathematics and physics, which can help you learn data analytics, machine learning tools, and other technological aspects easily. If you are a Computer, IT, or Software Engineer, then your existing software, hardware, networking tools, and knowledge in big data will help you embrace data science quickly.
Engineers who have worked for a long time in the industry might feel at ease while they are trying their hand at data science in the 21st century. But it is totally different for beginners. Engineers who started working just a couple of years might find it extremely daunting. The extreme void is because of their different inexperience in the market. Experienced engineers have a statistical mindset and reasoning, which is important in data science. On the other hand, freshers are not much into statistical point of view as they have just begun their career. To patch this gap, new engineers should work extra to become well-versed in data science in 2021. They should learn to generate hypotheses, analyze graphs, plots, and reasoning. Engineers should become experts in handling structured and unstructured data.
Besides planning for a shift from engineering to data science, engineers can also embrace the techniques of data science and streamline their current working process. As engineers are exposed to data constantly, their decision-making skills are already highly based on predicted big data outcomes. But dealing with massive data is different. Fortunately, data science can help you handle large data and take effective decisions based on that.
Engineers who have learned data science can easily connect the dots of the data ecosystem within a company or institution. Besides, learning data science comes with a list of advantages as listed below.
• Data science is evolving to be the backbone of decision-making. Engineers who have learned data science are responsible for both the works of a data analyst and data scientist.
• Engineers can understand coding better when they mend their skills with data science. They find easy and convenient ways to create abstract, broad, efficient, and scalable solutions.
• Learning data science comes with great financial rewards. Over a short period of time, engineers gain value and can demand a high salary or switch to a job with a high salary after learning data science.
Even if you don't want to carry on your job as an engineer, but want to work in data science, it can be very useful to have basic knowledge from engineering courses.
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