In this article, we are talking about data science and what important role mathematics plays in the field of data science. The scope of data science is increasing and, to pursue a career in data science, one can start by pursuing a Bachelor of Science in Mathematics from any recognized university.
Data Science is a detailed study of large amounts of data and providing meaningful information from the same. The inputs which are derived from the given data helps organizations in predicting data trends, identifying new growth opportunities, increasing efficiency, saving costs, etc.
Data Science is a combination of the skills and studies stated below:
· various scientific methods,
· processes,
· domain expertise,
· programming skills,
· knowledge of mathematics and statistics,
· Algorithms, etc.
These are useful in generating valuable insights from the data, which are helpful for industries.
- Data Scientist — Job Overview
Data Scientists help turn raw data into useful information. Data Scientist researchers analyze and conclude the data. They work closely with businesses to study their goals and requirements, understand their problems, and, based on that, they design models, create the algorithm, and infer data. A data scientist should present the valuable inputs effectively and be well-versed in machine learning, mathematical skills, statistics knowledge, coding, etc.
- Role of Mathematics in Data Science
According to my research, to build a successful career in data science, detailed knowledge of mathematics is a must. Mathematical concepts are required to study trends and patterns in data and infer insights from them. These insights then assist in algorithm creation.
Mathematics is the ground for all the disciplines of science. Almost every scientific technique has an in-depth concept of mathematics rested in it. Machine Learning, a part of data science, focuses on making computers capable of practicing automatically. But that will also require algorithms to learn data and make predictions. Hence mathematics in machine learning holds an important role too.
To understand concepts of the mathematics behind data science there are three main elements. They are as follows:
Linear Algebra
Linear Algebra is required at every point when you are into data science whether it is to write codes or to reduce data dimensionality; all models require computations through linear algebra. The most efficient calculations carried out by computer are using linear algebra.
Calculus
For data science, the understanding of calculus principles has to be there. Principles of calculus help in getting clarity on the effect of those principles on mathematical models. Calculus helps in maintaining the accuracy in the development of mathematical models.
Statistics
Data-driven decisions are taken by using statistical tools. Statistics and probability help convert raw data into new filtered data, after analyzing and inferring them.
Data Science — Future Career
According to India Today, Analytics-related Job opportunities are surging like anything; there is a possibility of 39000 new career opportunities related to analytics to be available by the year 2022. With such predictions in the picture, it has been realized by the organizations that data science is needed to survive the cutthroat competition.
Below are some job roles for Data Science Professionals:
· Data Scientist
· Machine Learning Engineer
· Machine Learning Scientist
· Applications Architect
· Data Architect
· Data Engineer
· Business Intelligence Developer etc.
I would suggest pursuing data science would help you outshine in your career as it holds a brighter future. The universities from which you choose to pursue your course also play a significant role in your career growth, and so make sure to select the top engineering college.
