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Data Science

How can a mechanical engineer become a data science professional?

Key takeaways: 

  • A mechanical engineer must have the right skills and experience. They should have strong analytical skills to process large amounts of information and find patterns. They should also be well-versed in programming languages and tools like Python, R, or Scala. 
  • They should also be familiar with machine learning models such as regression analysis, clustering algorithms, and decision trees. Also, they should know statistical methods such as linear regression, ANOVA, etc.
  • They must understand big data analytics tools such as Hadoop/Spark/Flink/MapReduce/Cassandra/HBase/MongoDB etc.
  • They should be able to work with different types of data, such as structured (e.g., relational databases), semi-structured, and unstructured.
  • Finally, they must understand how their organization uses data science techniques to make decisions that affect their business processes and operations.

It is easy to see why companies are so interested in hiring data scientists. The field has been around for decades but has only recently been recognized as an essential part of business operations. Data science is an umbrella term for several different practices involving computer programming algorithms to analyze large amounts of data and produce actionable insights on improving processes and products.

Mechanical engineers are perfectly positioned to use these skills because they already have experience collecting and analyzing data from their work on product design projects. Many mechanical engineers have already worked with software programs like MATLAB or Excel that can be used to manipulate numerical data sets into useful information. 

But how do I switch from mechanical engineering to data science?

Because of their training as mechanical engineers, many students tend to be good at solving problems through trial-and-error testing rather than relying on intuition alone (as many software developers do). This makes them excellent candidates for or want to know more about how to switch to a data science job involving extensive data analysis because they are able to identify patterns within large amounts of seemingly unrelated information without needing much guidance.

Many factors prove data science is related to mechanical engineering. Some of them Include – 

  • Use of Computers and Programming

First, both disciplines involve the use of computers and programming. In mechanical engineering, this is especially true, as most work done in the field involves computer-based analysis or simulation. It is also true of data science professionals, who are often tasked with creating algorithms based on the results of their studies.

  • Strong mathematics

Second, data science for mechanical engineers requires a strong background in mathematics (though not necessarily advanced mathematics). Data scientists need to understand basic statistics and probability, which requires some proficiency in math. Similarly, mechanical engineers must understand calculus and other higher-level math concepts to model real-world phenomena using computer simulations.

  • Needs and specifications

Mechanical engineers also need to understand how to create products that meet specific needs or specifications; this is similar to how data scientists must collect data from existing sources so they can analyze it later on to find patterns or trends which can be applied to solving specific problems, such as improving manufacturing processes.

How will the data science course help mechanical engineers in career switches?

Data science is an emerging field in the tech industry, and it is one that mechanical engineers can use to make a smooth and seamless career switch to data science.

  • Gain knowledge and value

Data science is a growing field, and it is not just mechanical engineering to data science. As more companies use data to make business decisions, they are looking for people with various backgrounds who can help them analyze that data. Mechanical engineers can take advantage of this trend by learning to apply their skills in a new context.

  • Knowledge in programming languages

If you want to make a career switch to data science, you will need to learn how to program and do fundamental data analysis. Although there are many programming languages, Python is one of the most common ones in the industry. If you are already familiar with Python or another language like Java or C++, then learning about machine learning algorithms will be easier!

  • Higher salaries

If you are considering a career switch to data science, you are probably asking yourself if it is worth the investment in time and money. Data scientists are paid an average of INR 14.2 LPA.

Moreover, employers are willing to pay more for data scientists who have experience and certifications. So if you are looking for a high salary and have the necessary skills, then becoming a data scientist could be a great investment.

  • Enhance decision-making skills

Data scientists need to understand how their work impacts others and how it can be used to improve lives. They must also know how to present their findings in a way that makes sense for different audiences. This means that data science will help you be better equipped to make decisions about their work and how it affects other teams or departments within an organization.

The transition from mechanical engineering to data science

Can mechanical engineers do data science? Mechanical engineers interested in changing to a career in data science should be prepared for a steep learning curve.

The career switch to data science requires an understanding of programming, math and statistics, as well as a new set of skills.

Here’s why –

  • Programming

Mechanical engineers are familiar with programming, but not the same way data scientists use it. Data scientists use programming to build programs and algorithms that can be used to analyze data. They also use it to build models, which are representations of real-world processes. Mechanical engineers must learn new tools, such as Python and R.

  • Math and statistics

Students who have studied math but haven’t studied statistics make up the question, “can a mechanical engineer do data science”. Data scientists use statistics to understand the relationships between variables in their data sets, which is essential for making sense of large amounts of information. 

These skills will help mechanical engineers understand how their data sets work together—for example, when one variable increases or decreases while another stays constant—and what these relationships mean for their company’s products or services.

  • Domain knowledge

The field of data science is relatively new, and as such, many skills need to be learned. Data engineers have to learn how to manipulate data and write scripts, while data scientists have to learn how to use machine learning algorithms and create models.

As a mechanical engineer, you’ve spent your whole life learning about how machines work, and that knowledge can easily be applied to data science. This means that you will be able to jump right into manipulating numbers and writing code without much trouble.

  • Visualization

Data visualization is a crucial part of data science; this is where the skills you learned as a mechanical engineer come in handy. You will need to visualize data to understand it better, so knowing how to make compelling visualizations with code will help you immensely.

Career opportunities

Data science is a field that’s constantly growing, so there’s never a shortage of opportunities. In this section, we will explore some of the most exciting data science career paths you can take in.

  • Data scientist

A data scientist analyzes, extracts and prepares data to help make better decisions. They are responsible for using their technical skills to turn raw data into something businesses and organizations can use. But how do you switch to a data science job? 

Data scientists often get a job with a computer science or mathematics background, but it is not required. Strong knowledge of statistics will suffice.

  • Data analyst

Data analysts use their skills to analyze large data sets and make recommendations based on their findings. They may also use their expertise to keep track of specific trends and changes over time, which can be helpful for business owners who want to ensure they are staying abreast of what’s happening in the market. Data analysts need a wide range of skills, including math proficiency and an understanding of statistics.

  • Data engineer

A data engineer is responsible for designing and implementing systems that process and analyze data. They are also tasked with collecting, cleaning, storing, and distributing data. Data engineers work with various software tools to develop data pipelines and automated processes that move data from one place to another.

  • Business analyst

Business analysts are responsible for analyzing large amounts of data to provide insights companies can use to make business decisions. But how do you switch to a data science job? These professionals may work in any industry jobs by having skills in areas such as data analysis, statistical modeling, market research, business process design and project management.

Why choose Online Manipal courses to become a data science professional?

Enrolling with the Online Manipal courses are one of the best ways to become a data science professional. These courses provide a comprehensive understanding of the subject matter and equip you with skills that can be used in any industry. The course also includes practical examples and case studies to help you get a better understanding of the subject matter. Industry experts provide the training with years of experience in their respective areas.

MAHE’s industry experts design online M.Sc. Data Science course. It covers all aspects of data science like machine learning, artificial intelligence (AI), deep learning, statistics, Big Data Analytics, etc., which will help you in getting hired by big companies like Google and Amazon. If you would like to move to managerial roles, prefer MAHE’s online MBA in Data Science.

You can pursue the course at your convenience, depending on your interests and requirements. Each module consists of lectures, videos, notes, quizzes and assignments that will help you learn at your own pace. Since there is no strict time schedule, you can take enough time to complete each module successfully before moving on to the next one if necessary!


The future of data science for mechanical engineers is bright. Several roles in the field don’t require years of experience as a developer or even any coding knowledge.

Online Manipal offers several courses designed specifically for professionals who want to transition from their current role into data science, including an Introduction to Data Science and Analytics course that teaches students how to use Python to analyze and visualize data sets. Enroll now!


Information related to companies and external organizations is based on secondary research or the opinion of individual authors and must not be interpreted as the official information shared by the concerned organization.

Additionally, information like fee, eligibility, scholarships, finance options etc. on offerings and programs listed on Online Manipal may change as per the discretion of respective universities so please refer to the respective program page for latest information. Any information provided in blogs is not binding and cannot be taken as final.

  • TAGS
  • data science
  • Master of Business Administration
  • Online MBA
  • Online MSC Data Science

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