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Dec 26, 2024
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2021-2022 Graduate Catalog [ARCHIVED CATALOG]
Data Engineering, M.S.
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Data engineering is the discipline concerned with the design of systems and use of analysis methods for the acquisition, storage, management, security, and processing of data. Data engineering incorporates a number of different fields including acquisition and storage system design, analytics, machine learning, statistics, security, and database management. Centering on the problems of both working professionals as well as researchers in the critical field of data engineering, the SMU program in data engineering serves the needs of both full-time and part-time students.
Admission Requirements
In addition to meeting the Lyle School of Engineering admission requirements for an M.S. degree, applicants are required to satisfy the following:
- A bachelor’s degree in one of the engineering disciplines, quantitative sciences, mathematics, or computer science.
- A minimum of one year of college-level calculus and an introductory course in probability and statistics.
- A minimum of two years of industry experience or submission of official GRE general graduate school admission test scores.
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Degree Requirements
In addition to meeting the Lyle School of Engineering degree requirements for an M.S. degree, candidates are required to satisfy the following:
1. Satisfactory completion of the core curriculum encompassing the four courses:
2. For the coursework-only option, satisfactory completion of six elective courses from the following list with at least three of the six courses at the advanced elective or 8000 level. For the coursework-only option with a specialty track, satisfactory completion of four courses from a technical specialty track, two additional courses from the following list, and at least three of these six courses must be at the advanced elective or 8000 level. For the thesis option, satisfactory completion of four courses from the following list with at least one of the four courses at the advanced elective or 8000 level, six credit hours of ENGR M.S. thesis credit, and the successful defense of the M.S. thesis. For convenience, the elective courses are organized under broad topic areas in data engineering.
(Any deviation from the stated requirements must be approved in writing from the student’s adviser and the MSDE program director.)
Foundational Courses Supporting Data Engineering
Data Acquisition and Sensing
Data Analysis Applications and Support
Articulation
All students entering the program are expected to possess knowledge equivalent to the following Lyle courses.
- CS 1341 - Principles of Computer Science
- CS 1342 - Programming Concepts
- ECE 2381 - Digital Logic Design
- ECE 3381 - Microcontrollers and Embedded Systems
- EMIS 3309 - Information Engineering
- EMIS 3340 - Statistical Methods for Engineering and Applied Scientists or ECE 3360 - Statistical Methods in Electrical Engineering
Students entering the program with an undergraduate degree other than those from the quantitative sciences, mathematics, statistics, engineering disciplines, or computer science may be asked to take one or more articulation courses. Such students will receive conditional admission to the program. Students must receive a grade of B or better in each articulation course to continue in the program. Credit from the articulation courses will not count toward the 30-hour M.S. degree requirements
Sample Degree Tracks
Any of the elective courses may be used towards completion of the master’s degree in data engineering with at least one course at the advanced elective or 8000 level. The courses comprising this requirement should be determined by the student’s background and experience, and approved by the student’s adviser. Sample tracks are given for guidance in developing an area of expertise within the wide scope of the data engineering field. The following are examples of appropriate tracks for a M.S. degree in data engineering where a student and their advisor would pick three electives and three advanced electives under each example track.
Data Engineering with Intelligence and Learning
Data Acquisition and Preprocessing
Data Engineering Research
Residency and Level Requirements
A minimum of 30 graduate credits must be earned toward an M.S. degree, of which at least 24 must be earned in residency at SMU. Up to six credits may be transferred with departmental approval. Of the 30 credit hours needed for graduation, at least nine credit hours must be 8000-level Lyle courses for the coursework-only option. For M.S. thesis students, the requirements are six credit hours of ENGR Master’s Thesis with an additional three hours of 8000-level Lyle courses, and all remaining credits in courses at the 7000 level or higher.
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