The data science industry is growing by leaps and bounds. Thanks to new developments in statistical techniques, machine learning, visualization, and more. The role of Data Scientists has evolved simultaneously. From a statistician to a data scientist to now neural network developers, data science has undergone an unprecedented transformation, resulting in what we collectively now know as data science.
Data science empowers companies to predict their state and prepare themselves better. The demand for data-driven decision-making is now more than ever before. One thing that can be attributed to this success is the constant research and development taking across the industry. The increasing demand for data science professionals corroborates the increasing inclination of companies toward data science at Universities and colleges are setting up data science initiatives to meet the demand for data science talent and push the frontiers of data science.
What is a data science initiative?
Data science initiatives are university and college programs that aim to develop data science talent by offering research and development and academic programs. The federal and state governments offer similar programs.
The following are a few prominent data science initiative programs:
1. University of Florida – Data Science Research
2. University of California, Berkeley – The Berkeley Institute for Data Science
3. Columbia University – Data Science Institute
4. New York University – Center for Data Science, VIDA (Visualization Imaging, and Data Analysis Center)
5. Northwestern University – Data Science Initiative
6. University of Washington – Data Science Research & Education
These programs are aimed at building the talent pipeline needed to meet the demand for data science talent. Similarly, organizations like the World Data Science Initiative offer similar data science talent development programs. As part of the initiative, the organization offer subsidies for universities. The initiative offers up to $300 million in subsidy. These subsidies can be utilized for accreditation and data science certification. World Data Science Initiative, for instance, offers universities and colleges to acquire certification from the Data Science Council of America (DASCA), a prominent certification body in the field of data science.
Further, data science initiatives offer bachelor’s and master’s programs in data science and related fields including machine learning, artificial intelligence, deep learning, robotics, etc. These programs aim to prepare the current workforce for data science-related roles. Some of the prominent areas which these programs aim to fill are natural language processing, data mining, computer vision, imaging, Big Data engineering, among others.
The other large side of data science initiatives is research. These initiatives offer to set up a center of excellence, allowing students and researchers to indulge in breakthrough research that aims to push the frontiers of data science. The Center of excellence boasts of state-of-the-art infrastructure and technology. These centers foster research that has made a significant difference in the data science industry. Healthcare analytics, bioinformatics, and Big Data are some areas that have seen a significant impact.
Harvard T H School of Public Health; NYU, Tandon School of Engineering — VIDA (Visualization, Imaging, and Data Analysis); The University of Michigan – School of Public Health, among other universities are few names that have made breakthroughs in research. The universities are actively involved in bioinformatics, computational biology. The research has applications in AIDS, Cancer, and other deadly diseases. Not to mention, this research are preparing talent at the same time.
Conclusion
Data science initiatives are programs that educational institutions run to accelerate the pace of data science talent development. Both, educational and non-educational institutions are involved with equal enthusiasm in these initiatives. These programs have paved the way for development in data science as well as creating a steady stream of data science talent required in the industry.
