The Road to becoming a Data Scientist - Learning Paths Explored
Data Science is one of the sexiest jobs of the century. The demand for data scientists is high, and the number of opportunities for certified data scientists is increasing. Every day, companies are looking out for more and more skilled data scientists.
Are you looking to be one?
In this article, we give you the recommended learning path and all that you need to be a skilled data scientist.
Who they are and what they do
The term “data scientist” is an industry recognized designation for a professional with high analytics experience, industry knowledge, and skills.
What is Data Science?
Data Science is a method of how you unify different concepts of subjects such as MATHEMATICS, STATISTICS, INFORMATION SCIENCE, COMPUTER SCIENCE etc. to analyse the phenomena of data to give insights. The other name for Data Science is “Data Driven Science”.
Who can be a Data Scientist ?
A Data scientist is sort of “jack-of-all-trades” for data crunching. Basically, 3 main skills a Data scientist needs to possess are mathematics/statistics, computer programming literacy and knowledge of particular business.
Core Knowledge Needed To Be A Data Scientist
Mathematics and Data Science – The core of building data product is the ability to view the huge volumes of data quantitatively. Building analytic models to solve business problems is usually hard math. Though statistics is an important part of data science, it is not the only type of math utilized.
Many inferential techniques and machine learning and linear algebra are used by data scientists. It is necessary for a data scientist to have an overall depth of knowledge in mathematics.
Technical and programming skills – Using technical skills to wrangle enormous data to create genuine solutions require complex programming skills. Data scientists need to be able to code – prototype quick solutions, as well as integrate with complex data systems. Core languages associated with data science include SQL, Python, R, and SAS. On the periphery are Java, Scala, Julia, and others.
Strong Business strategies – A data scientist must be able to view data through business lens. This helps translate the data observations made to solve business problems. Data scientists use the data insights as support to build better business strategies.
Additional Skills set needed to be Data Scientist:
Communication Skills: Statistics and Excel because Data Scientists should be able to present the data in a way that it communicates the results to the business users.
Business Skills: As said Data scientist is a “Jack of all trades” which means he need have knowledge on multiple subjects. They need to communicate with different people in the organization.
Problem solving skills: Data in business is all the number game. So its important to have problem solving skills. Data scientist should also provide solution suitable to the business with deep thinking.
Prediction Skills: A data scientist should Predict the future with the past information. He should have wider knowledge on algorithms to choose the right one to properly fit the business requirement.
Hacking: Its can be awkward when we say Data science involves Hacking. Hacking according to Data science means to manipulate text files at the command line, understanding vector operations and algorithmic.
Keywords: Data Science Institutes In Hyderabad.
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