Maths is the backbone for data science . Actually maths is a broader term . Therefore If we filter out maths word , there are few things where you need to brush up as data science learner . Probability , statistics , linear algebra etc are most required but there are so many other things apart from them which are also relevant to data science . In this article I will be more specific to the topics inside them . The only thing which I will recommend you if you are really interested to learn Maths Essential for Data Science is to bookmark this article and finish them . in short this article is a road map for Maths Essential for Data Science .

## Maths Essential for Data Science : Topics Overview

## 1.Linear Algebra –

As You already know most of the data science operations are performed in Matrixes . Under Liner algebra , You should at least know –

- Basics Matrix and vectors operations
- singular value decomposition (SVD) , Eigen Value and Eigen vector etc
- triangular matrix , identity matrix, square matrix and other special type of matrix .

#### Where to read Linear Algebra for Data Science-

#### Linear Algebra for Data Science – Machine learning – AI

#### Complete linear algebra: theory and implementation

## 2 . Calculus-

Calculus has wide application area in data science . Specially in deep learning and neural network it is must to have skills .Lets brief the the topic under the calculus umbrella which you should learn first –

- Concept of Maxima and minima.
- Concept behind – Functions of single variable, limit, continuity .
- Concepts of ordinary and partial differential equations.

As we all know , Few of us really like calculus but most do not . In order to realize its importance lets understand with Gradient descent .Gradient Descent is one of the elementary concept of Machine Learning . Do you know its completely on the top of gradient, derivatives etc.In order to understand this completely you must know the calculus basics .

#### Where to read Calculus for Data Science-

Calculus 1 for Beginners: Open Doors to Great Careers

## 3. Statistics-

I do not think , I need any more explanation on data science and statistics relation and importance . As statistics is one the most important area , So I will suggest you to go throw the below article for topic reference and reading material –

#### Where to read statistics for Data Science-

Complete Road Map to Learn Statistics for Data Science In Easy Ways

## Probability –

As you know , Probability is also equally important as statistics .We have also covered Probability in a separate article . Get the complete overview for probability topics overview and relevant tutorials reference here –

#### Where to read probability for Data Science-

Complete Road Map to Learn Probability for Data Science

## Discrete Math-

Most of the data science projects usually start with Proof of Concepts Right ? Discrete Mathematics is full of such theorems and methods which we use to proof some thing . Amazing thing which we ignore usually that most of the data structure concepts are built on discrete mathematics . Whether it is graphs , stack , queue or some others etc. So Discrete Mathematics is important from developer and data scientist both point of views right . Here are some important topics which are really important in context of data science-

- Concepts of Basic Proof Techniques like – induction, proof by contradiction etc .
- Concepts of Basic data structures- stacks, queues, graphs, arrays, hash tables, trees etc .
- Concept of Growth of functions

#### Where to read Discrete Mathematics for Data Science-

Discrete Mathematics: The Complete Discrete Math Course

## Optimization and operation research –

Under this umbrella you should know the below topics –

- Concepts of Randomized optimization techniques — hill climbing, Genetic algorithms etc .
- Constraint programming ,Linear programming
- problem formulation for optimization .

#### Where to read Optimization and operation research for Data Science-

## Conclusion –

To sum up ,I have tried to simplify this topic in easy words for you. Still its an two directional work if you think we can add some thing related to **Maths Essential for Data Science : Topics Overview **or simplify some thing which is explained already , comment below or send us an email . Most of us are already aware to these maths concept from the school days . Actually the difference between the level of studies is very clear . In school days we mainly focus on solving the maths problem .Moreover in data science , Now we have to frame real problem into data science problem followed by their solution using maths concepts .

**Data Science Learner Team **

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