The role of Mathematics in learning Data Science

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The role of Mathematics in learning Data Science

Advanced Mathematics is not about number crunching. It is more focused on telling the reason behind things, the systematic processes which make concepts a reality. And due to this, Mathematics plays a crucial and irreplaceable role in the field of data science.

Thus, if you aspire to learn data science to make a career in the field, you must have a strong understanding of mathematical concepts. You must be well equipped with pattern identification and designing algorithms if you look up to a data science career.

Besides defining a systematic approach, Mathematics is also necessary for learning the latest and most commonly used technologies in the field of data science, such as Machine Learning, Deep Learning, and Artificial Intelligence. This is because all these technologies derive their foundation from Mathematics.

We at Imarticus Learning offer a Certificate Program in Data Science and Machine Learning which helps you not only understand the concepts of data science but also help you build a stronghold on the mathematical concepts you will require during your data science career journey. Our course focuses on the mathematical branch of Statistics, which forms the basis of all data science tools and concepts.

Mathematical Concepts Which You Must Know As A Data Scientist

Following are some of the key mathematical concepts which you must be well versed in if you aspire to a data science career:

  • Probability

Probability refers to the mathematical concept that lets you evaluate the likelihood of an event. It comes in really handy for making future predictions based on data sets using the latest technologies like Machine Learning. As a data scientist, probability helps with the reasoning for your decision-making.

A large number of real-life data problems are solved by data scientists with the help of probability and its allied concepts like Baye’s Theorem and Theory of Central Tendency.

  • Hypothesis Testing

Hypothesis Testing refers to the statistical concept of testing a hypothesis concerning the assumptions made for a population parameter such as its mean, variance, etc. Data scientists use hypothesis testing in several real-world data problems, such as finding the average order value for an e-commerce website or how much fuel wastage is avoidable by a petrol pump.

It also allows data scientists to make reliable predictions, such as how much an investor can expect in return from a financial instrument. As an aspiring data scientist, you must clearly understand concepts like null and alternative hypotheses, p-value, test statistics, and significance levels. 

  • Linear Algebra

Data scientists use linear algebraic concepts of matrices and vectors to speed up their analysis processes. Linear Algebra also finds its basis in Machine Learning and Deep Learning. It allows you to model complex algorithms and represent complex data in a simplified manner for easy data interpretation and decision-making.

  • Calculus

Calculus plays a very fundamental role in developing forecasting models for data scientists. If you aspire to make a career in the field, you must understand how the derivatives of a function work. However, the good part is that, unlike in school and college, you need not do the algebraic calculations for calculus manually because, as a data scientist, you can use computers and other advanced technologies for solving differential equations.

  • Regression

Regression is a statistical concept that lets you estimate the relationship between various dependent and independent variables. It finds an in-depth use in the field of big data for estimating trends and forecasts. Some real-life examples in which data scientists make use of the concept of regression are the estimation of demand and supply, inventories, sales figures, etc. 

Our Certificate Program in Data Science and Machine Learning not only equips you with the above-mentioned mathematical concepts but also introduces you to the concepts of machine learning and data visualisation along with programming languages. In addition to the diversified yet focused curriculum, we also provide career services such as resume building, mock interviews, and Capstone Project. 

Take Away

Data Science is one of the most promising fields of the future regarding job prospects and career growth. And this is the reason why programs in data science certification in India are becoming highly popular. 

According to the latest Analytics India Magazine report, around 1,400 data science professionals in India earn more than Rs. 1 Crore annually! And with the advancement in technologies and the growing importance of data for analysing consumer behavior, the demand for data scientists will only grow in the coming times. 

Are you looking for some professional data science career advice? Contact us through chat support or visit our nearest training centres in Mumbai, Thane, Pune, Chennai, Bengaluru,Gurgaon and delhi.

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