Data Science in Mechanical Engineering – A Guide!

A strong background in Physics and Mathematics helps mechanical engineers in setting the best foot when it comes to transitioning to data science. They can easily learn the use of data analytics, machine learning tools, and other technological aspects of the domain. Before understanding how data science in mechanical engineering is useful, let us first know the individual periphery of both courses. 

What is Data Science?

Data Science enables the understanding and analysis of data as it is an integration of various fields such as informatics, statistics, data analysis, or other related fields. It requires the use of theories and techniques from various disciplines such as Mathematics, Computer Science, Statistics, Information Science, and Domain Knowledge.  

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What is Mechanical Engineering?

An amalgamation of mathematics and engineering physics concepts, this branch of engineering intends to explain the analyzing, designing, manufacturing, and maintenance of mechanical systems. This engineering discipline requires a core understanding of subjects such as Mechanics, Material Science, dynamics, thermodynamics, electricity, and structural analysis. 

Relationship between Data Science and Mechanical Engineering

Despite being quite different fields, data science and mechanical engineering overlap in some areas, and individuals with expertise in both of them will be in demand in the near future. Nowadays, intelligent systems and techniques are used to develop different components of a machine or device to enhance performance and for optimization. 

Currently, there are a limited set of tools for mechanical engineers and these have set the benchmark for processes like machine control, hardware designs, etc. Though there are a few excellent software like ANSYS, Abaqus, MATLAB, CATIA, etc, they are complex and it becomes difficult for managers or engineers to track if something goes wrong in a project. Thereby, leading to disasters like financial losses, loss of time, money, and manpower. 

This is when Data Science comes into the scene as it comes with a solution to make online updates for relevant analysis, predictions, and visualizations for the performance of thousands of factors such as equipment, environmental conditions, etc. Since data science employs techniques from different disciplines like mathematics, computer science, and statistics, mechanical engineers are very familiar with them and it becomes easier to understand advanced concepts of data science in mechanical engineering.  

Applications of data science in mechanical engineering

The applications of data science in mechanical engineering are listed below:

1. Biomechanical Applications

2. Control Engineering Applications

3. Robotic Applications

4. Solid Mechanics Application

What is the best mode of learning while switching to MS in Data Science after Mechanical Engineering?

There are various modes of learning available for both fresh graduates and working professionals, who want to upskill themselves in the field of data science. Enrolling in an in-person classroom session abroad or an online curriculum with live instructor-led learning is one of the best ways to switch to MS in Data Science after Mechanical Engineering. 

While an in-person classroom offers its share of benefits such as a wholesome learning environment and real-time engagement, live online training with instructor-led sessions can also be effective if the students are unable to attend the classes physically. While most of the universities abroad offer only an MS degree in data science, the University of Washington provides two options for students to become Mechanical Engineer turned Data Scientist. 

1. Master of Science in Mechanical Engineering (Data Science)

Students with an undergraduate degree in ME or a closely related field are eligible for this course.

2. Master of Science in Engineering (Mechanical Engineering: Data Science)

Students with a non-ME academic background are eligible to get admission to this course.

No matter whichever college or university a student chooses, it is essential to ensure that the course they are offering is industry-relevant and boosts a proper understanding of data science tools and concepts. 

Advantages of studying data science for mechanical engineers

Mechanical engineers can increase their demand in the job market by mastering data science, thereby expanding their chances to switch to a better-paying job. Every organization needs a data scientist since several decision-making processes are built on data. The advantages of studying data science for mechanical engineers are as follows:

1. Gain know-how of various programming languages to develop effective and scalable solutions.

2. Effectively manage massive datasets and enhance decision-making skills based on data science results.

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Tools that a beginner should learn as a beginner in Data Science

The most popular tools that are used in the field of data science are Tableau, Spark, Python or R, MS Excel, and Hadoop. Python is one of the most sought-after languages when it comes to programming for data science. R is also a must-learn programming language. It makes better business-ready reports using Rmarkdown. On gaining more experience, individuals can use a platform named Shiny which enables users to interact with data sets and analysis.