Data Science

1. What is a Data Scientist? Data scientists are big data wranglers, gathering and analysing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. They analyse, process, and model data then interpret the results to create actionable plans for companies and other organizations. Data scientists are analytical experts who utilize their skills in both technology and social science to find trends and manage data. They use industry knowledge, contextual understanding, scepticism of existing assumptions – to uncover solutions to business challenges. A data scientist’s work typically involves making sense of messy, unstructured data, from sources such as smart devices, social media feeds, and emails that don’t neatly fit into a database. How to Become Data Scientist 1. Earn a bachelor's degree in IT, computer science, math, physics, or another related field; 2. Earn a master's degree in data or related field;

2. 3. Gain experience in the field you intend to work in (ex: healthcare, physics, business). Data Scientist Education Requirements There are many paths to landing a career in data science, but for all intents and purposes, it is completely impossible to launch a career in the field without a college education. You will, at the very least, need a four-year bachelordegree. Keep in mind, however, that 73% of the professionals working in the industry have a graduate degree and 38% have a PhD. If your goal is an advanced leadership position, you will have to earn either a master’s degree ordoctoratedegree. Some schools offer data science degrees, which is an obvious choice. This degree will give you the necessary skills to process and analyse a complex set of data, and

3. will involve lots of technical information related to statistics, computers, analysis techniques, and more. Most data science programs will also have a creative and analytical element, allowing you to make judgment decisions based on your findings. Data Science Specializations Data science is needed by nearly every business, organization, and agency in the country and across the globe, so there is certainly the chance for specialization. Many data scientists will be heavily specialized in business, often specific segments of the economy (such as automotive or insurance) or business-related fields like marketing or pricing. For example, a data scientist may specialize in helping car dealerships analyses their customer information and create effective marketing campaigns. Another data scientist may help large retail chains determine the perfect price range for their products. Some data scientist work for the Défense Department, specializing in the analysis of threat levels, while other specialize in helping small start-up businesses find and retain customers. Why is it so hard to become a data scientist?

4. The nature of data science is a hybrid of many disciplines. Where it composed of different subject areas like math (i.e., statistics, calculus, etc.), database management, data visualization, programming/software engineering, domain knowledge, etc. In my opinion, this may be the primary reason why people interested in jumping into the entry-level data science career often feel completely lost. Most people don’t know where to start because you may lack in one area completely or multiple areas depend on one’s educational background and work experience. Where to learn Data Science? We provide best data science professionals, who decided to dedicate their careers in building Analytics and Data Science Course In Gurgaon. We feel passionately about creating next generation data science community All of these are examples of analytics at work in real time with increasing usage of mobile devices and digitization across the globe, advantages of investing in cutting edge analytics are unlimited. If you feel similarly about creating data science ecosystem, feel free to get in touch with us on