The studies towards MSc Degree in Information Systems Engineering with Focus on Data Mining and Business Intelligence are aimed at training researchers and professionals with strong analytical skills in the areas of Data Mining, Data Science, Predictive Analytics, Big Data, and Business Intelligence. The studies in Data Mining and Business Intelligence are mainly targeted at the BSc graduates of Information Systems Engineering, Software Engineering, Computer Science, and Industrial Engineering. The degree requirements include writing a research thesis in a relevant area and eight mandatory and elective courses including at least six courses in Data Mining and Business Intelligence.
Data Mining and Business Intelligence deal with automatic data analysis and knowledge extraction from internal and external sources with the goal of supporting the organizational decision-making process. This field has become a critical factor in today’s competitive environment and it serves all tiers of management from operational decisions to strategic planning. The studies are meeting the evident need for professionals in Big Data, Business Intelligence, and Data Mining.
Program of Study
The studies towards MSc Degree in Information Systems Engineering with Focus on Data Mining and Business Intelligence comprise 36 credits including eight mandatory and elective courses of 3.0 credits each and a Thesis (12 credits).
Supplementary Courses without credit
A student admitted to the program, specifically without a degree in Information Systems Engineering, Software Engineering, Computer Science, or Industrial Engineering, may be required to take supplementary courses until the end of the second semester. One can take supplementary courses from the courses offered by Ben-Gurion University or equivalent courses from other accredited universities subject to recommendation by the departmental teaching committee and approval by the Faculty teaching committee.
Courses:
Mandatory Course
Research Methods in Information Systems (3 credits)
Core Courses
Core Courses - one should choose four courses out of the following six courses:
Applied Machine Learning (3 credits)
Advanced Methods in Data Mining and Data Warehousing (3 credits)
Text Mining and Web Content Mining (3 credits)
Applications of Learning Algorithms in Information Systems (3 credits)
Mining Massive Datasets (3 credits)
Recommender Systems (3 credits)
The student should take elective courses out of the graduate courses offered by the department to complete 24 credits from the following list of courses:
• Advanced AI
• Advanced data bases
• Complex Networks
• Data acquisition and representation
• Decision support systems
• Decision support systems for medicine
• Diagnosis in multi-agent systems
• Intelligent systems
• Knowledge based systems
• Machine learning methods for attack detection
• Network security
• Planning and automatic decision
• Search methods in AI
• System security engineering
The lists of supplementary, mandatory and elective courses are subject to change.
Thesis
Every graduate student has to do a research thesis under the supervision of a department member. The research proposal is subject to approval by the supervisor and the graduate teaching committee. The thesis is evaluated by the rules of the Faculty of Engineering Sciences. The thesis will be in the area of Data Mining or Business Intelligence.
Who should apply?
BSc graduates of Information Systems Engineering, Software Engineering, Computer Science, Industrial Engineering, and similar disciplines from accredited universities. Students without a degree in Information Systems Engineering, Software Engineering, Computer Science, or Industrial Engineering, may be required to take supplementary courses at the discretion of the graduate teaching committee.
