B.S. Computer Science - Data Mining Concentration
Mathematics, Computer Science and Physics Department
NEW Concentration for Fall 2014
We are now witnessing a new era in modern information technology, namely, the era of Big Data. Huge amounts of data are continuously generated every minute. Data sources range from social networking sites, stock trading sites, news agencies, insurance companies, and search engines, to sensors in meteorological and climate systems, patient monitoring systems, and acquisition and control systems that can be found in cell towers, cars, airplanes and power plants. With these enormous amounts of data, systems and techniques are needed to extract knowledge, information and patterns for prediction, forecasting and decision making purposes.
As an example of the amounts of data that is being generated, a recent study estimates that Google receives more than 2 million search requests per minute, more than 48 hours of video are uploaded on YouTube every minute and over 680,000 pieces of information are shared on Facebook every minute.
Data mining is the process of analyzing large sets of data from different perspectives and extracting useful information. This information can be used to predict behaviors and future trends, which is crucial in increasing revenue and cutting costs for businesses.
Businesses use data mining to discover certain patterns and relationships in data which are then used in the decision making process. Data mining is currently being used to detect fraud, perform market basket analysis, analysis of sales trends, and marketing campaigns.
There is a great demand for data mining professionals, in fact there will be a shortage of 140,000 – 190,000 people in the field by 2018, as well as a shortage of 1.5 Million managers and analysts who can understand and make decisions using big data.
Students planning to major in computer science with a concentration in data mining will take courses in computer science, and mathematics. The concentration was designed based on guidelines provided by the ACM SIGKDD Curriculum Committee.
The concentration is designed to prepare students to work in fields related to management and analysis of data such as data mining, machine learning and information retrieval. Students will gain the necessary knowledge and understanding of the methods and techniques of data mining and reasoning with data preparing them for the job market where they will apply these methods and techniques in real life situations.
Laila Khreisat, Ph.D.
Department of Mathematics Computer Science and Physics
Fairleigh Dickinson University
285 Madison Ave - M-ZN2-02
Madison, NJ 07940
ZEN 250, Room 257