Basic pre-requisites for data scientists
Tags: datascience, machinelearning, NLP, beginners
Published: 2020-06-04 18:19:03

A lot of technological advancements and its benefits in data science field has attracted lot of individuals to make career in data science. It is always a good thing in tech field to know essentials while proceeding to pursue career in particular tech side.This eases and help the individual to decide the pathway till the target and gives him an idea about "How much efforts he has to put in" to reach to the final goal. So this post aims to provide a piece of information about the essentials to become data scientist.


**1. Approach and understanding**
  * According to me, the most important thing in tech field is to understand and figure out the way to approach to programming problem. 
  * Once an individual gets to know the approach, then he/she can easily solve the problem. One can find it easy to design an algorithm with this quality.
for eg. if i have to solve an NLP problem, then my approach would be like this,

       a] Data gathering
       b] Data cleaning
       c] Figure out good representation
       d] Classification
       e] Inspection
  * And if we come up to the programming thing, it can be learned easily because its all of syntax and different methods which you find on the internet.

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**2. Slight business understanding**
* To jump up in data science, it is very important that one should have basic business understanding and be aware about " for which business they are going to work", because the problems that are going to be solved with the help of data science varies from business to business.

For eg. if i am working for zomato or swiggy, then my possible role as data scientist will be to analyze the reviews of customers about the food and delivery services, which can help the company to make the further improvements. So i must have food delivery industry kind of sense.


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**3. Languages like python, R**
* The versatility of these languages make them one of the most used languages for data science. It can take various forms of data, prepare it for processing and with the help of algorithm, can provide particular insights and results
* Besides, there are massive libraries available for most of the processes which eases the work of data scientists and make the operations perform in no time
* provide functionality for mathematics and statistics

So, it is very important to have knowledge of these languages.

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**4. Familiarity with machine learning algorithms**
* It is also considered as equally weighted as of other pre-requisites, because ML algorithms help in predicting the possible results
* ML algorithm help in drawing important aspects from the data use the concepts of mathematics and statistics
* It is expected to atleast know the workings of algorithms, so then they can be easily implemented

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**5. Visualization tools(Tableau, PowerBI)**
* These tools are very helpful for data analysts which can help them to draw and visualize data, so that they can design particular strategy for organizations based on results from visualizations
* The tools are handier for data manipulations and attractive visualizations can be designed with the help of these tools
* These tools can help to monitor businesses and get instant rich and wonderful dashboards on any devices

So learning these tools can help you remain one step ahead.

Keeping these things in mind would help you to progress towards field of data science and can help you in designing the pathway.

Any feedback or suggestions would be greatly appreciated.