Πέμπτη, 22 Ιουνίου 2017

How to become a data scientist – Complete Guide

How to become a data scientist – Complete Guide





How to become a data scientist – Complete Guide





5 Things to learn to becom data scientist
5 Things to learn to become data scientist Infographic

If you are looking for a High Paying Quality job profile in IT
Industry  . Data Scientist comes up in your wish list . When I started
searching about How to become a data Scientist. I got so many
informative article over internet. These article were full of
information but quite massive and distributed.

So ,In this article I have mentioned best way to learn data science
in very compact and serial way .If you follow all these tips , You will
be a Data scientist in very less efforts.   Actually, Data science is
combination of so many interrelated fields like Machine Learning, Data
visualization and Programming. It also includes Mathematics and
Statistics principles. This combination and its complexity create
massiveness and confusion in reader’s mind.

There are so many varieties in sub skills under Data Science like Programming language (python vs r), Machine learning algorithms
(Supervised Machine Learning Vs Unsupervised Machine learning). Which
skill should get higher priority for learning is the major pain area for
data science learner. If you are experiencing the the same, this is the
right place for solving all your problem. We have created a straight
road map to assist you in your confusion of How to become a data
scientist.



How to become a data scientist image
How to become a data scientist image



How to become a data scientist –  Complete Guide

As per the data scientist job description available across the
industry, we can divide the skill set in five major classes. I have
arranged these five skills in the order of priority. We have also
created a road map in the form of info graphics for your better
understanding. These five steps are best way to learn data science.

1.Brush up your Basic Mathematics and Statistics for Data Science –

Probability and statistics are fundamental tool required for every
predictive analytics. It is badly used in every corner of data science.
Especially Machine Learning Data Mining is the field where you cannot
take any step without having dirty hand in Mathematics and Statistics.

You may find Free eBook on statistics for data science by just
clicking the below link. Probability and statistics interview question
for data science is must covered topic in this section as well for
better performance in your job interview. Every Data Scientist job
description contains separate column of Probability understanding as
required skill.

2. Learn r Programming | python for data science-

You have to opt one programming language in every data science project. The possible combination for learning are –

  1. Learn r Programming
  2.  python for data science
  3.  java for data science.
This is the second step in the series of best way to learn data
science. If you are doing any data science project, you need data. Data
Analyst can use or produce data  by external file source like excel or
you have to fetch via some API call using some programming language.
Finally , You have to use at least any programming language to
accomplish these task .I will recommend you to refer our article Why Python for Data Analysis . This article is focusing over python but after reading it you can relate it with other programming language.

If you want to make your hand dirty with python and you are looking for

a short overview type article , Python essentials in 5 minutes will be the best article for you .

3. Learn Applied Machine Learning Algorithms for Data Science

Machine Learning algorithms and Trained tool are essential for data
science. There are so many tools available where you can train your
machine learning model. This Model you be integrated in your existing
Data science project. Data science project. Lets understand it with a
example , Suppose we have to create a price prediction algorithms for
any financial firm and we have 10 year past data only. We will build the
model using some market logic for the prediction of next year . If we
some how able to make automatic feed back system in our existing system
to add the current real outcome as experience .So next time we will have
11 year training data . In the same way as the time passes our system
will be more  precise in predictive analytics . This approach is called
 machine learning where machine start learning it self with its past
experiences .

I will suggest you to take over view of Machine Learning Library . This will improve your understanding .



4. Learn Data visualization Tool for Data Science

Data Scientist mine the data and extract some meaningful result out
of it .These result could be any pattern , any indicator or something
else . To understand the hidden information out of the huge raw data ,
You have to use some data visualization tool. In fact , We have so many
data visualization toll available all around us . Companies from
different industries are using these tools very frequent . Some of them
are very popular and frequent like-

  1. Qlik Sense and QlikView
  2. D3.js
  3. Tablea

5. Learn Big Data Technologies for Data science-

this comes last but quite effective.Specially If you want to become
full stack data scientist . There are so many big data tool and
technologies  . Hadoop is open source framework for Big data . Spark
with java and Scala is also quite frequent use framework . There is a
complete list of required Big Data Tool in Data science .For Beginner , I
will suggest to learn Hadoop first .

Finally , If you learn all these technologies , You can start your
career as a Data Scientist .I mean these all skill are essentials for a
Data Scientist  . Along with this , If you are dealing with text
analytics You may use Natural Language Processing . Natural language
Processing is NLP in short . NLP as a short and trendy word in field of
technology. All big and innovative companies are working on NLP .
Facebook and Google also come in these list .

Lets Zoom in Machine Learning Data Mining  . Machine Leaning is
itself a branch of  Artificial Intelligence .Programmers and application
Designer are using machine learning data mining , Data science , AI in
their existing Application .This Integration are migration their
Technology  into new era.There are so many tools like Amazon Machine
Leaning , Azure ML Studio , Apache singa are in trend.

Anyways , Lets conclude all. Data Scientist is some one who is good
at Maths , Programming and Analytics .These three are major branches in
their itself . Their combination creates a meaningful data .
Unstructured data is majorly available around us . Most Of the time we
create a unstructured data unknowingly.For Example the video of  our
activity is a unstructured data in itself.To handle this a major pain
area in field of Data Science . So If  you learn unstructured data
technologies with data science , You are future ready product.

End notes

I think , We have have done enough discussion over the topic How to
become a Data Scientist . If you want to explore more on Machine
Learning , You can refer our article What is Machine Learning ? .

Δεν υπάρχουν σχόλια:

Δημοσίευση σχολίου