While other analytical degree programs adapt to the advent of Big Data, the MSDS program within the Computer Science department is designed from the ground up to focus on the latest systems, tools, and algorithms to store, retrieve, process, analyze, visualize, and synthesize large data. This special two years MSDS professional program consists of 6 foundational classes and 6 Elective Classes. Every student is required to complete before graduation a competitive one semester Capstone Project. A central goal of the program is to build systems that integrate in a coherent manner the full data cycle- from data gathering to data visualization and data synthesis aided by computer-human interaction. The six foundational classes expose students to the identification of questions whose answers can be aided by data retrieval, data cleaning and data modeling tools, plus specialized algorithmic and statistical processing, machine learning, pattern recognition and interactive visualization tools. A faculty supervised CapStone class is dedicated to building a prototype system where students exercise the skill set acquired in the other foundational classes.Check details »
Have a future career as a professional data scientist
Market: As modern information technologies relentlessly generate voluminous and complex data, algorithmic analytical tools with solid foundation in computer science, statistical theory and computer human interaction and communication have become indispensable to industry and society in general. This trend has created a strong surge in the demand of professional data scientists.
Essential data scientists skills include computational thinking, interactive data collection, pattern exploration, statistical analysis, summarization, visualization and sense making. One of the central goals is to create and integrate computerized tools that enhance decision making in social, scientific and economical endeavors aiming to improve citizens quality of life.
Receive solid training in algorithms, probability, statistical learning, computing systems, data mining, machine learning and visualization.
Acquire a deep understanding of the nature of uncertainty, modeling, performance checking and decision making.
Implement interactive tools for data analysis and sense making.
Develop strong communication and leadership skills.
Ten courses, in 3 semesters and two capstone projects (full time).
Possible summer internshipsCheck details »
Admission Requirements We are offering admission to students if they satisfy the following admission criteria: Courses in an accredited university with an equivalent grade of B or better in Multivariate Calculus, Discrete Math, Linear Algebra, Statistics, Probability Proficiency in : (C/C++, Java) or (Python - Perl) and a Unix/Linux Shell Or An undergraduate degree in Computer Science from an accredited university with a GPA greater than or equal to 3.25 (out of 4).
Students with undergraduate degrees in Statistics, Mathematics, Physics, Engineering and other Sciences with a GPA above 3.5 (out of 4) , may be considered for temporal admission and will be placed in undergraduate bridge classes on Data Structures and Algorithms, Data Bases, Operating Systems and Computer Architecture. After successful completion of these remedial classes (with a grade of B or better) they will be granted full admission into the MSDS Program.Check details »