{"id":30056,"date":"2021-04-19T17:04:00","date_gmt":"2021-04-19T11:34:00","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/quality-education-to-cope-with-shortage-of-data-science-talent\/"},"modified":"2024-12-06T10:43:35","modified_gmt":"2024-12-06T05:13:35","slug":"quality-education-to-cope-with-shortage-of-data-science-talent","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/quality-education-to-cope-with-shortage-of-data-science-talent\/","title":{"rendered":"Quality Education to Cope with Shortage of Data Science Talent"},"content":{"rendered":"\n

As uses of technology continue to advance into new areas every day, we find ourselves living well within the age of big data. In fact, a 5000% growth was recorded in the amount of data created, captured and copied in the last decade<\/a>. In such a scenario, where it has become commonplace to refer to data as the new oil, data science has emerged as a dominant field that serves as the basis of decision-making in prominent businesses or the development of advanced technologies. Data science, thus, has also become part of aspirations of several professionals who aim to be at the forefront of data-driven initiatives at any organization. <\/p>\n\n\n\n

Data Science and Analytics Demand by Industry (Source: IBM)<\/em><\/p>\n\n\n\n

Is there a Shortage of Data Science Talent?<\/strong><\/h2>\n\n\n\n

The demand for data science and analytics talent is immense in the job market. This reflects in the fact that hiring for data scientists increased by 46% between 2019 and 2020<\/a>, even at a time where organizations cut down on hiring in general due to the COVID-19 pandemic.\u00a0 However, equally factual is the shortage of data scientists in the market. While this shortage has resulted owing to several factors, a major factor here is the lack of high quality training programs in data science that could translate one\u2019s learnings from a course into a successful career.<\/p>\n\n\n\n

Quality Education: The Pathway to Becoming a data driven Decision-Maker<\/strong><\/h2>\n\n\n\n

An effective or essentially high quality training program in data science is built upon certain cornerstones. Not only should the learning take place under the guidance of academic experts in the domain, but it should also be complemented by industry-relevant training which is best achieved via hands-on learning. <\/p>\n\n\n\n

Learning from leading academicians in the Domain<\/strong><\/h3>\n\n\n\n

When dealing with a domain with a subject matter as intricate as data science, the journey is made fairly easier and worthwhile when those teaching you are leading figures in the domain. The faculty in leading institutions of the world carry a knowledge bank that is a combination of theoretical expertise as well as a vast research experience that bridges the gap between theory and practice. Being part of a training program under expert faculty also ensures that one is learning via a carefully crafted, industry-relevant curriculum that would take into account the latest developments in the field. <\/p>\n\n\n\n

Hands-on Learning that prepares you for the Industry<\/strong><\/h3>\n\n\n\n

Regardless of whether one is aspiring towards data science at an early stage in their career, or they are looking to make a career transition, experience demonstrating industry-relevant skills will give you that extra edge when being considered for job roles in the domain. <\/p>\n\n\n\n

Doing projects that look at real life problems is a great way to build your portfolio in this case. An effective training program should therefore include provisions for you to indulge in hands-on learning and test whether the knowledge you have gained has enabled you to solve real-life business problems. This experience is further enhanced if one also has access to a mentor who is an experienced data science practitioner. <\/p>\n\n\n\n

Masterclass on Applied Data Science Program - Meet the faculty: Prof. Devavrat Shah, MIT<\/strong><\/h2>\n\n\n\n

If these insights on quality education for aspiring data scientists have garnered your interest, you can now hear more about it from a world-renowned MIT Professor, Devavrat Shah<\/strong>. Devavrat Shah is a professor with the department of electrical engineering and computer science, MIT. He is a member of the Laboratory for Information and Decision Systems (LIDS) and Operations Research Center (ORC), and the Faculty Director of the MicroMasters in Statistics and Data Science program at IDSS.  His research focus is on the theory of large complex networks, which includes network algorithms, stochastic networks, network information theory and large-scale statistical inference. Prof. Shah was awarded the first ACM SIGMETRICS Rising Star Award 2008 for his work on network scheduling algorithms. He received the 2010 Erlang Prize from INFORMS, which is given to a young researcher for outstanding contributions to applied probability. He is currently an associate editor of Operations Research.<\/p>\n\n\n\n

<\/a><\/p>\n\n\n\n

In an exclusive masterclass, Prof. Devavrat will elaborate on MIT Professional Education\u2019s Applied Data Science Program<\/a>. If you are looking for more information about the program, curriculum or mentored learning, save your seat<\/strong><\/a> and you can hear about it from Prof. Devavrat Shah at the webinar in a conversation with Milind Kopikare<\/strong> (President, Great Learning).<\/p>\n\n\n\n

The session will cover:<\/p>\n\n\n\n