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IS 698 Special Topics in Information Systems (3 credits)

Periodically, our faculty offer courses that cover topics addressing specific issues within information systems. These “special topics” courses offer our online master’s students a unique opportunity to delve into subject matter that is closely relevant to particular areas  of interest within the IT professional community and is derived from research conducted by faculty here in the IS department of UMBC.

Special topics courses, when offered, meet advanced course requirements and count toward your degree. These courses are subject to limited enrollment and prerequisite requirements.

Note: Students that have taken IS 698: Semi-Structured Data Management cannot take this class.

  • Summer 2015– Instructor Dr. Kip Canfield: NoSQL Databases
    • Database management systems have been dominated by relational systems for over 30 years. Due to changes in hardware, bandwidth, and use case, systems are changing. Multiple processors, gigabit network speeds, and the Internet as a platform for distributed systems are changing the way computing gets done. Relational databases is not being superseded, but many so-called ‘non-standard’ system architectures are now being developed and deployed for specific application classes. We will look at a developing category of such systems sometimes referred to as ‘NoSQL’ systems that have become very important for semi-structured, distributed information for web applications.  We will cover current systems from conceptual and practical standpoints. We will read papers on representative systems and do simple programming against the databases.  Students need a computer that they can install software on in a virtual machine so it does not impact you regular system and is easily deleted.  Prerequisites are a previous course in programming and in databases.
  • Spring  2015 – Instructor Dr. Lina Zhoul: Social Media Application and Analysis
    • This course emphasizes the potential of social media space for various applications and the basic analysis of social media data. Social media have brought about a wealth of user-generated content and relationship networks on the Web. The online word-of-mouth has significant impact on\ businesses and organizations. Social media also strongly influence individual users, transforming how they retrieve, organize, store, and share information, how they create and use knowledge, how they interact with one another, how they build new relationship and maintain existing relationship, and so on. This course will help students understand the phenomenon of social media and basic analysis methods and application of social media. This course will provide students with concepts, methods, knowledge, and skills to use and manage social media effectively. It will also prepare students to formulate social media strategies and innovative social business models.
  • Spring  2015 – Instructor Dr. Anthony Norcio:  Readings in Advanced Structured Systems Design
    • This course is an advanced study of structured systems development. Emphasis is on strategies and techniques of structured analysis and structured design for producing logical methodologies for dealing with complexity in the development of information systems. The course focuses on reading scientific papers from the relevant scholarly literature on various topics of systems design. The students will discuss thesetopics based upon their readings of the scientific literature. This course objectives are to introduce the issues, principles, methodologies, and theories of advanced systems design and to prepare students for research and/or professional work in this area.

 

  • Fall 2014 – Instructor Dr. Kip Canfield: Discrete-Event Simulation (DES)

    • A course in the theory and practice of discrete event simulation as used in operations research.  We will use the python programming language for the simulation exercises each week. The course covers data preparation, system modeling, simulation design, analysis of output, and programming in Python.  Applications are drawn primarily from manufacturing, service systems (like banking), and healthcare.The prerequisites are statistics and elementary object-oriented programming in any language.
  • Fall 2014 – Instructor Dr. Aryya Gangopadhyay: Introduction to Data Science

    • This course provides a comprehensive introduction to data science. It covers the foundational principles of data science including statistical inference and exploratory data analysis, machine learning algorithms, data visualization, and big data. Concepts are explained in the context of real life examples. The course includes hands-on exercises using open source software platforms          

                   Prerequisite for all sections:  IS 633 (or its equivalent