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Course Criteria
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3.00 Credits
The course covers the fundamental concepts related to the design, use and implementation of relational database systems, with emphasis on creation of data models based on the entity relationship data model. In addition, students will receive in-depth training of the languages and facilities provided by database management systems with query languages, specifically SQL. Additional topics include a survey of techniques related to database recovery, database security, database management in various environments and distributed databases.
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3.00 Credits
Software Engineering and Project Management deals with Software Development Life-Cycle Methodologies. SDLC methodologies consist of gathering requirements on, implementation, testing, documentation, deployment and maintenance of software. The software development life cycle (SDLC) is a framework defining tasks performed at each step in the software development process. SDLC is a structure followed by a development team within the software organization. It consists of a detailed plan describing how to develop, maintain and replace specific software. The life cycle defines a methodology for improving the quality of software and the overall development process.If the student takes CPSC 468 for the undergraduate program, he/she can take CPSC 668 for additional credits.
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3.00 Credits
This course provides an overview of concepts, techniques, algorithms and applications in machine learning, including supervised learning (e.g.: classification and regression), unsupervised learning (e.g.: clustering and dimensionality reduction), and learning theory (e.g.: bias/variance; regularization and feature selection). Moreover, the course will include research projects that will require writing computer code, conduction experiments, and writing papers. If the student takes CPSC 480 for the undergraduate program, he/she can take CPSC 680 for additional credits.
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3.00 Credits
This course covers the theoretical and practical fundamentals of Big Data. Students will learn the essentials of big data analytics including Big Data Characteristics, Management, Storage, Processing, and Analysis. The course is designed to involve hands-on experience with big data frameworks such as Hadoop MapReduce and Spark. If the student takes CPSC 485 for the undergraduate program, he/she can take CPSC 685 for additional credits.
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1.00 - 3.00 Credits
A unique and specifically focused course within the general purview of a department which intends to offer it on a "one time only" basis and not as a permanent part of the department's curriculum.
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1.00 - 6.00 Credits
A workshop is a program which is usually of short duration, narrow in scope, often non-traditional in content and format, and on a timely topic.
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1.00 - 3.00 Credits
A Selected Topics course is a normal, departmental offering which is directly related to the discipline, but because of its specialized nature, may not be able to be offered on a yearly basis by the department.
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1.00 - 3.00 Credits
Independent Study courses give students the opportunity to pursue research and/or studies that are not part of the university's traditional course offerings. Students work one on one or in small groups with faculty guidance and are typically required to submit a final paper or project as determined by the supervising professor.
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3.00 Credits
This is a capstone course that requires students to complete a health informatics project. The project must be approved by MSHI faculty by no later than the end of the first week of the course. Students will be invited to propose their own projects or create one in collaboration with MSHI faculty.
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3.00 - 9.00 Credits
This course offers an individually designed health informatics experiential learning opportunity within a cooperating enterprise. The experience provides an opportunity to integrate, apply and expand upon the skills acquired in health informatics coursework. Learning objectives, specific activities and an anticipated timeline must be approved by the professional supervisor and faculty supervisor prior to registering for the course.
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