Do You Know What Does It Take To Become A Healthcare Data Scientist?


    First we need to know what Data Science is?

    Data Science is nothing short of magic and a data scientist is a magician who performs tricks with the data in his hat. Now, as magic is composed of different elements, similarly data science is an interdisciplinary field. You can consider data science to be an amalgamation of different fields such as Data Manipulation, Data Visualization, Statistical Analysis, and Machine Learning. Each of these sub-domains is equally important when it comes to data science.

     What Will It Take To Become A Healthcare Data Scientist?

    Well, it is no different from being a regular data scientist but with a very high focus on healthcare data. Till date, the majority of data science courses and degrees focus on data science in general, and using the foundational skills, one can make a data career in healthcare, bioinformatics, medical/genomic science, health economics and other associated fields. Health Data Science is a pretty new discipline, and it’s a blend of epidemiology, statistics, mathematics, informatics and computer science.

    There are specialised Data Science Course programs offered by universities, mostly at the postgraduate level. For example, there is a Masters In Health Data Science, an eighteen months post-grad program offered by Harvard University. MSc Health Data Science will help you develop innovative skills needed to unlock knowledge from complex health data to address some of the biggest health challenges that we face across the globe today. There is also a master’s program here at Georgetown in health informatics and data science. 

    There are courses in India as well, such as Master of Health Data Science (SRM University), and Master of Science – Health Informatics & Analytics from The University of Trans-Disciplinary Health Sciences and Technology (TDU). The idea of such programmes is to create graduates who can manage and handle huge, messy healthcare data sets from various sources, and to bring them all together in an analysable format. It provides knowledge on analysing the data using statistical machine learning approaches and drawing useful insights from the data. 

    Masters in data science receive training in multiple areas, including quantitative methods, applied regression, analysis statistical, statistical inference computing, machine learning, statistical consultation and collaboration, and epidemiology methodology. The main programming languages that are used in the most health data science courses include a mixture of Python and R, and SAS also in some cases. 

    Qualities of a Data Scientist

    If you want to learn Data Science, you should be aware of the various strengths of a Data Scientist. In this Data Science tutorial, you will also see that there are a lot of skills that you need to master in order to become a successful Data Scientist.

    Some of the skills that an accomplished Data Scientist possesses include technical acumen, statistical thinking, analytical bent of mind, curiosity, problem-solving approach, big data analytical skills, and so on.

    If you have any doubts or queries related to Data Science, do a post on Data Science Community.

    How to Learn Data Science to Be an Expert?

    If you want to be an expert Data Scientist, then you need to practice the following things:

    • Familiarize yourself about the real-world Data Science problems

    Like one famous person once said that the whole world is one big data problem. So, as a Data Scientist, it is your job to learn more and more about various Data Science problems in the real world. This way, you will have an inside understanding of this domain.

    • Participate in Data Science forums and competitions

    There are a lot of forums that are regularly hosting Data Science contests and competitions for Data Scientists. You would do well not only learn Data Science but also participate in these highly exciting contests. That way, the knowledge that you get from this Data Science tutorial can be built up and put into practical use.

    • Regularly work on huge datasets

    There is a huge amount of data that is available on the Internet. It could be real data or just a practice dataset. But, whatever be the nature of this data, it will be beneficial to work on it to implement your knowledge and get hands-on practice in the domain of Data Science.

    • Have a collaborative and interactive approach

    Since Data Science is a very vast field, in the initial days, it would be good to have a collaborative approach to learn Data Science. That way, you will learn it in an interactive way and will be on your way to becoming an accomplished Data Scientist.

    • Practice every day and gain a definitive edge

    So far in this Data Science tutorial, you have learned Data Science, but that would not be enough. If you want to build your skills and hone it to perfection, then you need to practice every day since, as we all know, practice makes a man perfect. To learn Data Science, the rule is not much different; you need to practice a lot to achieve perfection.

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