Can one become Data Scientist in 2 months?!
How to become a Data Scientist in duration of just 2 months? this question is very popular as it is the mostly asked by the aspirants, while the fact is that nobody can ever become a data scientist it just simply doesn’t work that way. In fact, even a senior Data Scientist will get to learn unique things on an everyday basis because there will be something new to learn in the field everyday. So how much of knowledge is enough for one to begin as a Data Scientist? and how much time does it going to take? Let us discuss about all this in detail down below.
How to become a Data Scientist?
It is not easy to become a Data Scientist but neither difficult! it is like learning any other field in computer science but it demands one’s absolute dedication and efforts. It generally takes 6–7 months of training for one to get ready for the field of Data Science, it is a multi disciplinary field containing various concepts wrapped together, it takes time to study all of them. Let us see what will one get to study in Data Science.
Python, R programming, SQL, Scala, Tensorflow, Matlab, tableau are the tools that are very necessary and concepts like Statistical approach and mathematical modeling are fundamentals of Data Science.
Statistics
It is a Mathematical Science pertaining to data collection, analysis, interpretation and presentation. Statistics is used to process complex problems in the real world so that Data Scientists and Analysts can look for meaningful trends and changes in the Data.
Mathematics
Linear Algebra, Calculus, Statistics and Probability, these are the important math concepts involved in Data Science.
Python
Python language is frequently used in data science as it is highly productive language with simple programming syntax’s and easy code readability, English like commands makes it easily understandable.
Projects
Projects take half weight in a course because only through working in them one will get to have glimpse of actuality of Data Science. A trendy and useful set of projects will do wonders.
R programming
It is a free software environment for statistical computing, the graphics for statistical computing are supported by R foundation.
With the help of this languages one could easily merge with Statistics oriented fields.
SQL
SQL is the mainstream language that is used to access database because it can work with any database. It will help to store the data in an organised and logical manner, its statements are used for updating data on databases, or retrieving data from various databases. Oracle, Sybase, Microsoft, SQL server, all such uses SQL. Database is the main backbone for anything in the technical world, as data is the new fuel to the current generation, Database handlers are in high demand in every field that involves technology.
TensorFlow
It is mainly used for Classification, Perception, Understanding, Discovering, Prediction and Creation of Data. It is an open source AI library that uses data flow graphs to build models. It allows developers to create large-scale neural networks with various layers.
These are the tools and concepts that one must study to begin with Data Science.
The efficient way to study Data Science
I recommend anyone to look out for a good Data Science course, it is the best way to get the knowledge of the field. But again choosing a course has now became tricky, because there are many courses of such in market making one enough confused about what course to select. A course of quality training and absolute assistance for a reachable price is offered by Learnbay, it is helping students to easily and efficiently get started in the field.
