Data Science – The most sought-after degree in academic institutions

Chair of the Planning and Budgeting Committee, Prof. Yaffa Zilbershats: “In recent years, data science has become an extremely influential field in economics and hi-tech in general and in academic research in particular. The ability to cope with big data requires unique skills that combine mathematical, statistics, and computer capabilities, and we therefore view authorization of the bachelor’s and master’s study programs in data science, and training as many graduates as possible in the field as being of prime importance.”

The CHE has completed its planning of the academic development of the multiyear program for 2017-2022. As part of the planning process, the funded academic institutions submitted the curricula that they wish to implement in the coming years to the CHE and PBC.

The innovative programs in data science are prominent among the study programs submitted by institutions of higher education. Of all curricula authorized for submission as part of the multiyear program, the largest number was in data science – a total of 19 curricula in data science (10 curricula for a bachelor’s degree and 9 for a master’s). This program was authorized for the first time as a complete bachelor’s degree in 2015/16 at the Technion University.

Data science is a new field of research in both Israel and the world and in recent years that provides tools and skills for analyzing and greatest possible utilization of data so as to extract new knowledge , among other reasons, with the goal of supporting decision-making processes. The curriculum requires students to learn algorithms and technologies for analyzing broad and varied data bases (big data) in a wide range of knowledge domains. The degree programs respond to a clear need of the economy and therefore, the institutions have hurried to submit requests to implement these curricula during the current five-year plan.

We note that in the institutions’ request to authorize the curriculum, the quantity and availability of data created in various formats (text, pictures, audio, video, sensor data, etc.) have grown significantly in recent decades. At the same time, there have been developments in dedicated hardware for media, data storage and processing, and the large selection of new methods for data analysis and processing (such as deep learning) has grown, allowing the current speedy development of the field. A sophisticated analysis of these data can reveal templates and models that would not otherwise have been discovered and make it possible to reach new conclusions in a wide variety of fields, some with a high implementation potential.