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Skillset, topics, projects and virtual internships for DS

This post is for those who are beginner and do not have any idea about topics that they need as a beginner DATA SCIENCE/ DATA ANALYST.  I am also facing the same problem before a year ago and till date I have some relevant knowledge about data science and also have some projects.  People are saying the we need so many skills like Mathematics, Programming language, some cloud concepts too. Actually they are right. Being a Data Scientist is not like being a web developer or a front-end developer that have limited skill set.  In this post I will tell you the exact topics that you need to learn at beginner level. MATHEMATICS Descriptive Statistics, distributions, hypothesis testing and regression analysis. Bayesian Thinking, conditional probability, priors, maximum likely hood. Vectors and matrices Matrices operations Eigenvalues and eigenvectors Linear and non linear functions Multivariable calculus  PROGRAMMING LANGUAGE(Python or R)    Data types, String oper...
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Topics and Algorithms in Data Science

In my previous posts, I’ve told about What is Data Science, different fields of Data Science like medical field, industrial field, education field is also involve in it as data is everywhere so we can say that “Data Science is in every place where data exist.”

I have also told about different types of data that we deal in Data Science field like structured, unstructured, continuous, discrete. It is very convenient to deal with structured data (Data generally given in tabular format) but in case of unstructured data, it takes some efforts (because its may be video, audio or text or the combination of these).

Take an example of a webpage as may be it contains image, texts, audio or video files etcetera. So from this data exploration of insights will be a quite complex task.
These are some of things which I discussed on my previous posts.


Now let’s take a look of Data Science topics and some of Algorithms.

Regression

It is one of the simplest topic of Data Science. It works on structured data. By knowing some past information, telling about the future insights or telling about the insights between any fraction.

The value of one variable is depend upon another variable. And applying some algorithms we find the value of our desired (targeted) variable.

Ex . suppose any person hire a cab and cost for every mile is 10. Here miles(distance) is independent variable and cost is dependent variable.
 So
           Cost = 5 x distance,
                                                with the help of this equation we can predict the value for different distances (In further post we will learn how to make a regression model using Data Science libraries and Python programming language:-)
Data Visualization-

It is the best way for understanding of insights . It is an art of representing data in the front of others with clarity and it is also easy to understand. It is the key element to telling the people what you really want to express them.


Besides this there are also so many topics like neural networks, deep learning (advance version of neural networks) , machine learning including supervised, unsupervised and reinforcement, classification, clusters, recommendation and Algorithms  like KNN (nearest neighbour), SVM (support vector mechanism), Decision tree and many more.

These all mentioned topic will be surely cover in upcoming posts.


Thanking you.

If have any query, feel free to connect -
https://www.instagram.com/kavyansh.pandey

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