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Who is Eligible for Data Science?

  • July 04, 2023
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Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 17 years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

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Who is Eligible for Data Science?

Nowadays, data science has become more significant in everyone's lives. No matter if the person is a professional in the industry or has no background in data science. The study of data science teaches you how to collect data, analyse it, assess it, and alter it to produce the intended outcome. But what qualifications must one have to become a data scientist? This post will be very helpful to you if you are interested in starting your career and want to work in the fascinating subject of data science. Are you qualified to take this stage, as this will indicate? Let's begin by examining who qualifies for data science. The following criteria will be used to determine data science eligibility.

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  • Education

    Education plays a great role in getting into the field. Suppose you want to become a data scientist. In that case, you can get a degree in statistics, mathematics, computer sciences, and social sciences because the current scientist has a degree in these subjects. More than 80% of data scientists have master's degrees, and more surprisingly, more than 40% are working who have done a Ph.D. in one of the related subjects of data science. So if you have a master's or bachelor's degree in any of the mentioned subjects, then you are on the right path. You can make your career in data science as you are eligible to enter into the industry of data science. Because what you have learned in your degree will be useful for you and you can learn new skills easily and quickly. It does not mean that you cannot learn data science if you have no degree in the relevant field. You can learn, but you need to give more time to learn it as you have to start it from basic concepts.

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  • R Programming

    You must have in-depth knowledge of one of the technologies used most commonly in the industry if you are interested in mastering data science. You should be familiar with a programming language like R because roughly 40% of data scientists utilise it to address various issues. Although this language is challenging due to its intricate algorithms, you may learn it by taking one of the many online R programming language classes that are readily available. To be qualified for data science, one must at least have a basic understanding of the most popular programming languages.

    Because the majority of a data scientist's work involves computer or technical components, you might require some of the following technical abilities to succeed as an excellent data scientist. Therefore, you might not be qualified to learn data science.

  • Data Science

    SQL Coding

    Even SQL has not a significant position in data science. However, it is still expected that a candidate who wants to join the data science field must have the capability to write queries in SQL that may sometimes be proved complex. It would help if you learned data science as it has very short and concise commands that can save the time of the people and work easily and quickly. In this way, you can understand relational databases, and it also helps you make your profile more attractive. So to become a talented data scientist, you should learn SQL.

  • Machine Learning

    Many data scientists are not well-versed in the methods and tools of machine learning. You should be familiar with the machine learning process that incorporates regression and analytics if you want to become a well-known data scientist. You will accomplish this by finding solutions to issues that other scientists are unable to. As a result, you might make more money than other specialists since machine learning uses various methods to solve problems. It would be beneficial if you were familiar with machine learning techniques for handling large amounts of data. If you have the skills to use machine learning algorithms to solve issues, you will be qualified.

  • Visualization of Data

    Nowadays, every organization has a lot of data that needs to be organized efficiently and compactly. If you know the tools of data visualizations used to see an image and get deep insight from it, you will use this knowledge to boost your career in data science. In this topic, you have the skills to find out an easy way to present a complex and large dataset. You can participate in the competitions and quizzes to get more experience.

  • Un-supervised data

    The unsupervised data that the data scientists work with. You need the ability to work with unstructured data if you want to become a data scientist. You can apply to become a data scientist if you have the courage to present data as helpful and the skills to manage and analyse non-normalized data.

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    Non-technical skills

    To become an expert in data science, you also need to possess a number of non-technical talents. Because non-technical abilities are important in a subject as well, technical skills are not the only thing that count. If you don't want to enter the gateway of data science, you must take the following factors into account.

    • You must be curious about new things. You won't last very long in data science if all you rely on is your degree. Because data science is a subject that is always changing, you should prepare yourself to compete for change and keep learning.
    • You just need to consider the issue you resolved because that is what your solution shows. You are qualified for data science if your solution can foresee the direction of business.
    • If you want to advance your career, you must be able to interact with the organisation in a language that is understood by it.
    • You need effective teamwork to understand the demands of the business.
    • Before entering the profession, learning from the resources that provide data science will help you qualify for a successful job.

    A person is qualified to work in the data science sector if they possess all of the aforementioned abilities.

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