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Data Science

Data Science

Data Science is an incredibly vast industry. So, if you want to find a job for this branch, you need to equip yourself with some necessary skills and knowledge. Today, JT1 will introduce you to some information about Data Science.

Data Science

What is the definition of Data Science?

Data Science develops based on a combination of mathematics and IT that are represented by statistics or machine learning majors. It is separated into three stages: create and manage data systems, data analysis and transform these analytics into the value of an action.


Workflow to a Data Scientist

To become a Data Scientist, you need to know the specific workflow:

  • Data Capture: Scientists collect data by the extract from a company's database, scan from a website or access an API.

  • Data Manage: Organize and manage data, including deleting and removing redundant, unnecessary data.

  • Exploratory Data Analysis: Find different sources to analyze and present data, from which to find prototypes, problems or opportunities for further research.

  • Final Analysis: Dig deeper and data to answer specific questions for the area in charge, and refine to perfect predictive models to give the most accurate results.

  • Report: Present existing analysis results to the manager. Besides, you also need to convert and save analysis results into

  • Besides, you need to convert and store your analysis results into some kind of text so that other members of the department or customers can easily understand & use it.

Important professional skills to Data Science

To become a good Data Scientist, you need to improve some professional skills including:

  • Python: Python is known as a public language programming and easy to study. Python supports a large number of deep learning libraries such as Tensorflow, Keras, sci-kit-learn,... To get started with Data Science, Python is one of the ideal programming languages.

  • R: R is a statistical model language very popular with Data Scientists. It also provides for scientific activities of various data through its extensive libraries.

  • SQL: SQL is an important element to get started with Data Science. It is used to extract and retrieve data. Besides, it also is designed to manage data in the relational database...

  • Big Data: Big Data is an important technology and a small part of Data Science. Normally, a Data Scientist must cope with large amounts of data, knowledge of Big Data is very essential

  • Java: In more in-depth computing, Python is known as a scripting language and Java is known as a programming language. Many industries require knowledge, not only script but also programming language. Understanding Java will enable you to tune and maintain large data platforms that are written in the same language.


Besides, there are a few other skills you need to cultivate such as


The statistical form is considered as the core of Data Science. If you want to develop works Data Science, you must have incisive knowledge about different topics of statistical as logical statistics and descriptive statistics.


The mathematical concepts such as linear algebra, calculus, and probability are the most important concepts in Data Science. So, if you ensure knowledge about these concepts, it will help you very much with the role of Data Scientist.

Analytical thinking

Analytical thinking and solve problems are two important requests for any position in data science. So, you must have the knowledge and suitable creative thinking to create methods and use different tools to perform it.

The following information is needed to help you have a better overview of data science as well as methods to meet your current job needs.

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