In the Cloud Computing job market, there are ample job opportunities to work as a Full-stack Developer, Java Developer, Cloud Engineer, Software Architect, Data Scientist. Therefore, for a good career in this field, it is necessary to start learning AWS or Azure to start with. However, there are only a few large major players as employers in this field, namely:īut in the near future, there is room for more players as this field has enormous potential to grow.ĪWS is leading in the race although Microsoft Azure is neck-to-neck with AWS in competition. Most of the large organizations use Cloud Services and the demand for Cloud Computing is increasing day by day. It has got great advantages like lowering IT costs, start using required applications in minutes, easily scale capacity, instead of going in for costly hardware upgradations, etc.Įven at home, we regularly use some kind of cloud computing services such as applications like Gmail, subscription services like Netflix, or cloud storage like Dropbox. hosted on a Remote Data Centre managed by a Cloud Service Provider. This is a very smart way to utilize vast computing resources, like Applications, Servers, Data Storage, Developmental Tools, etc. University of Michigan: Applied Data Science with Python Certification.īerkeley Executive Education: Data Science Online Purdue University: Post Graduate Program in Data Science. LinkedIn Learning: Foundation Course in Data Science ().ĮdX (edx.org): Basic and Advanced Courses from Harvard, MIT, UC SanDiego, and other universities.Ĭoursera (): Basic and Advanced Courses from IBM, Google, and some reputed universities. It finds its application also in various other fields, including consumer goods and retailing, construction, communication and media, education, government, etc.Īccording to Builtin (), the following are the top Data Science companies:Īs per, the global data science platform market size was valued at USD 3.93 billion in 2019 and is expected to expand at a compound annual growth rate (CAGR) of 26.9% from 2020 to 2027.ĭata Science uses the knowledge of Probability, Statistics, Excel, Business Analytics, and software languages such as Python and R. Gaming: data science is used to figure out customer reactions to various games and accordingly making improvements in gaming models. Pharmaceuticals: data science is used extensively for all clinical trials and choosing people for such trials other than using it in the process of developing new drugs. Travel Industry: creating customer profiles based on segmentation, offering personalized experiences to the customers according to their needs and preferences has been made possible by using data science.Įnergy: since this industry is prone to major fluctuations in project cost and prices in the market, data science is employed to minimize such risks by using various predictive models. Healthcare: with the help of pattern recognition, analytics, statistics, and deep learning algorithms, data science makes healthcare more efficient.
and for avoiding any major equipment failure.
Manufacturing: data science helps the manufacturing process in a big way to streamline the whole manufacturing process implementing artificial intelligence and predictive analytics etc. Therefore every major company with large-scale operations would require people with data science skills to manage their big data in order to have a competitive advantage in the growing markets and hence such people will always be in high demand by various industries that are growing in the near future.įinance/Banking: data science helps in risk assessment and monitoring, avoiding fraudulent behavior, tracking all payments, claims, customer analysis, customer experience, among many other such business operations. This requires skills drawn from various fields such as computer science, statistics, mathematics, graphic design, information visualization, domain knowledge, etc. Data Science has therefore become one such industry that is growing by leaps and bounds. Such constantly growing big data needs thorough, critical as also timely analysis to create actionable insights for solving company or customer problems and also to generate ideas for the future growth of the company. All the organizations daily generate a huge volume of new data in the form of digits, texts, audio, video, images, etc., that we call Big Data that traditional processing software cannot manage.
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