Master program in Data Science - About
The explosion of Big Data has reached every part of modern life, and there are remarkable opportunities for data analysts and scientists. The global community of Information technology uses data science to decipher data that inform the decisions leading the economic growth. The demand for data scientists who can interpret that data will remain high.
Princess Sumaya University for Technology (PSUT) offers highly ranked and innovative programs that fill the gap between Academia and the market needs. During a two-year master program in Data Science, PSUT prepares the students for the dynamic and expanding world of Big Data and Data Science. Graduate students will acquire the skills necessary to help enterprise-level companies harness data and discover insights for competitive advantages. Students who graduated from this program are expected to do predictive analytics, create truly data-driven businesses, analyze structured and unstructured data, etc.
The curriculum of this master program has four main pillars built based on the role of the stakeholders in this field as following:
1) Data business-people are most focused on the organization and how data projects yield profit. At the entry level, the student will perform the junior duties of blending and cleaning data and preparing basic predictive models.
2) Data developers focused on the technical problem of managing data, i.e., how to get it, store it, and learn from it. At the entry level, the student will work with Hadoop as well as structured data.
3) Data architects are responsible for the entire process of analytics: from extracting and blending data, to performing advanced analyses and building models, to creating visualizations and interpretations. This is a more senior role for innovating new types of predictive analytic use cases, data products, and services.
4) Data Researchers, who are innovating data science at its most and publish their results. The program should provide foundational statistical theory, foundational programming skills, data modeling, Machine Learning, Big Data concepts and Toolbox, and business modeling for all these stakeholders.