The increased growth of data throughout the industries represents the growing need for opportunities in data science.
According to multiple reaches, there will be a wide variety of job opportunities available for professionals with data science skills. These include job roles with tech giants including Amazon, Facebook, Google, and Netflix utilizing data science techniques within the product offerings.
As a result, retail, finance, agriculture, government, IT, and healthcare sectors will increasingly start using data science techniques to improve businesses.
Therefore, data science professionals need a solid foundation and expertise in data science. And with the ongoing dearth for talent in data science, the world will need data science initiatives to fulfill the skill gap.
The World Data Science Initiative (WDSI) aims to generate more than 250,000 data science talents by 2022. There is a need to come up with such initiatives that can help technology schools and thousands of universities build the largest talent pool in data science worldwide.
Why WDSI is relevant for you?
To help you with the cause, WDSI is bringing together some of the world’s leading institutions involved in the technology sector and even education project bodies of the United Nations along with the World Bank and their personnel – data science professors, researchers, education regulators, and data science educators lend a hand to develop the next generation of data scientists and data technologists.
Considered to be one of the largest development projects across the globe, WDSI projects are willing to grant over USD million in subsidies for institutions. These subsidies can further help such institutions get accredited and help students of the institution get certified. WDSI is also considered to be an advanced vendor-neutral data science standards across the world. Touted as the world’s biggest talent development project in data science, WDSI received registrations from over 30 higher-education institutions from 23 countries.
Most of these institutions are looking forward to setting up centers of data excellence within their campuses. These centers of data excellence will further be called the International Centers of Data Science. Such centers project to offer programs in varied technology fields that include data science, AI, and machine learning.
The need for data science subsidies for institutions
Rapid advances in data generation have outpaced the ability to extract knowledge from these large amounts of data, creating a significant bottleneck to discover the need for more talents in data science.
Data science subsidies for institutions are crucial for multiple reasons. This includes creating a global of data scientists, data analysts, data engineers who can be trained and certified at the same time. The development of data science talents aims to spread across 14 global regions from across the world.
- Western Europe
- Central Europe
- Eastern Europe
- Oceania and Australia
- South Asia
- East Asia and APAC
- West Asia
- Southern Africa
- Central Africa
- West Africa
- East Africa
- South America
- Central America
- North America
Subsidies for universities and institutions offered by WDSI are for nations that are still emerging and are under-developed. At WDSI, they will get the opportunity to adopt the highest standard in data science. These subsidies include covering the costs that are involved in advanced learning resources, accreditation, and student certification. The grant or subsidy does not cover charges for the salary of the staff, fee for any type of external consultant, hardware, equipment, computer, third-party software, and infrastructure.
If you’re looking to register at WDSI, you need to keep a note of certain points. For instance, WDSI does not encourage or offer any type of financial assistance in cash to any type of beneficiary institution. Also, they do not follow the policy of releasing the subsidy amount right after the application has been approved.
Businesses are increasingly demanding data scientists, how prepared are you?
