The Master of Science in Data Science and Knowledge Engineering program (32 units) prepares students for professional practice or further study in data science, data analytics and knowledge engineering. It provides breadth and depth in the essential topics of data management, data mining, statistics and information systems. The program includes an independent research/development project.

Core Requirements (9 units)

EGR501 Engineering Resrch and Practice

This course is an introduction to the graduate study of engineering. Engineering mathematics and linear algebra, as needed for graduate study, will be covered. The Christian worldview and its perspective on advanced engineering will be examined through readings and reflections. An introduction to the topic of research and development will be provided. A presentation requirement using the Assertion-Evidence approach will be introduced. (3 units; Fall/Spring)

Clement, Larry W.
01/11/2021 M 5:00 PM - 8:00 PM Engineering 229

EGR506 ENGRing Rsrch and Dvlpmnt Method

This course is an introduction to research and development in the fields of engineering. Methods for properly researching a topic, collecting and processing data, drawing conclusions and presenting results are discussed. Special attention is paid to the process of technical development as opposed to research. Co-requisite: EGR501 (3 units; Spring/Summer)

Kim, Mark Sun
01/11/2021 T 5:30 PM - 8:30 PM Engineering 230

CSC525 Advanced Database Systems

This course will engage the student in essential database topics. The course assumes a basic familiarity with relational databases and SQL. The course will advance the student’s knowledge and skills in areas like database systems, database design, concurrency control and transactions, advanced SQL techniques, and data warehouse design. (3 units; Spring)

Data Science and Knowledge Engineering Requirements (17 units)

DSC521 Enterprise Architecture

This course equips students for strategic thinking with respect to IT-enabled transformation in modern organizations, through an end-to-end Strategic Management Process. This course provides a practical experience approach by positioning the students at the high-point of the Information Technology leadership activity, where goals and priorities are set and implemented. During the course students will lead a complete IT Strategic Management Process, think and behave strategically, exploit opportunities to employ leading-edge technologies, and deliver the right business value with IT. (3 units; Fall)

DSC523 Enterprise Data Communications

This course explores state-of-the-art computer communication infrastructure from protocols and protocol architecture to organizational management issues. Special focus areas from TCP/IP Internet communication, protocol design, wireless data networking, to networked applications are studied. The emphasis is on business managers and implementers to design, realize and operate advanced networks that provide efficient and reliable services to users. Topics include data science, data communications, application software, networking, and organization management theory. (4 units; Fall)

DSC530 Experiment Design for Data Sci

This course covers the most essential features of experimental research design and the measures associated with it. Principles and procedures involved in collecting, organizing, analyzing, presenting, and interpreting data from quantitative experimental design inquiry are primary areas of examination. Both descriptive and inferential statistical approaches are presented, e.g., describing data, its frequency, measures, and presentation to discrete and continuous probability, analysis of variance (ANOVA), linear and multiple regression, time series and forecasting, quality management and decision theory. Lectures focus on developing tangible understanding of experimental design and corresponding analytic models, and interpreting research results. Laboratory exercises will focus on using programming statistical software for data analysis and presentation. (4 units; Spring)

DSC541 Geogrphc InfoSys and Visualizatn

This course investigates complex spatial data ecosystems and their respective impact on geographic information system (GIS) solutions. Student develop comprehensive GIS knowledge as applied to working with geographic information. Formal definition and key functions that distinguish GIS from other information systems are presented and discussed. Historical development of innovative and collaborative geographic information tools that assist with managing the challenges associated with positional data are reinforced. Knowledge and skills acquired via application of the concepts of GIS are assessed by completing a series of lab assignments and a culminating research project. (3 units; Fall)

DSC550 Data Mining

This course examines at the entire knowledge discovery process. The focus on cutting edge, interesting data mining techniques that can be used in a wide variety of settings (business, science, web analytics, etc.). Topics include algorithmic details, implementation issues, advantages and disadvantages, and many examples of data mining. We will also include the newest topics, such as big data methods and deep learning. The course is a practical, hands-on course, covering knowledge discovery entails, the different groups of algorithms and their usefulness and shortcomings. The course culminates in a real-world project accomplished with open-source tools. (3 units; Summer)

Thesis/Project Requirement (6 units)

EGR507 Research and Development

This course is a continuation of graduate research and development in the fields of engineering. Faculty will supervise the research and measure progress of the work. May be repeated three (3) times for credit. Prerequisite: EGR 506. (3 units; Fall, Spring)

Jung, Helen
08/24/2020 - Online
Jung, Helen
01/11/2021 - Online

EGR508 Documentation and Presentation

This course completes the required graduate research and development sequence in the fields of engineering. The project work or research will be completed, fully documented and presented using the Assertion-Evidence approach to a group of faculty, peers and observers. Prerequisite: EGR 506. (3 units; Fall/Spring)

Jung, Helen
08/24/2020 - Online
Jung, Helen
01/11/2021 - Online