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Nov 23, 2024
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2017-2018 Catalog [ARCHIVED CATALOG]
Data Analytics and Systems Engineering, BS
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 Return to: Programs
Learning Outcomes
The College of Engineering and Applied Science has established the following educational outcomes for the Bachelor of Science degree in Data Analytics and Systems Engineering (DASE).
By the time of graduation, students are expected to demonstrate:
- An ability to apply knowledge of mathematics, science, and engineering
- An ability to design and implement algorithms to analyze large data sets and interpret results
- An ability to understand the systems engineering life-cycle process, and systems architecture and its relationship to system design
- An ability to function on multi-disciplinary teams
- An ability to identify, formulate, and solve engineering problems
- An understanding of professional and ethical responsibility
- An ability to communicate effectively
- The acquisition of the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and social context
- A recognition of the need for, and an ability to engage in, lifelong learning
- A knowledge of contemporary issues
- An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
Objectives
The educational objectives of the Bachelor of Science degree program in Data Analytics and Systems Engineering are statements that describe the accomplishments of graduates 3-5 years post graduation:
- Illuminate-lifelong learning in Data Analytics and Systems Engineering. Alumni are expected to learn new engineering technologies as needed and pursue graduate school to technology careers, including but not limited to technical development, project management, and technical sales.
- Investigate-demonstration of Data Analytics and Systems Engineering principles. Alumni should have the ability to find and access information relevant to an application under development and have the ability to understand and approach various engineering problems and convert them into engineering products.
- Innovate-creative application of Data Analytics and Systems Engineering principles. Alumni should be able to apply the theory and techniques of Data Analytics and Systems Engineering to innovate real-world solutions.
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Degree Requirements
The Bachelor of Science degree in Data Analytics and Systems Engineering requires the following:
- Completion of at least 128 credit hours
- Participation in the Exit Interview
- A minimum of 2.0 grade point average in all EAS and CU courses taken
Mathematics (21 Credit Hours)
Basic Science (12 Credit Hours)
- Complete 3 credit hours of any biology chemistry, astronomy, climatology, ecology, geology, meteorology, oceanography, or physical sciences course.
Business/Economics Courses (6 Credit Hours)
Programming Courses (9 Credit Hours)
Introductory Courses (6 Credit Hours)
Engineering Foundations (10-12 Credit Hours)
Social Sciences and Humanities (9 Credit Hours)
Studies in the humanities and social sciences serve not only to meet the objectives of a broad education, but also to meet the objectives of the engineering profession.
College of Engineering and Applied Science students are required to take social sciences and humanities courses in order to be more aware of social responsibilities and able to consider related factors in the decision-making process.
- GPS 1010 - Gateway Program Seminar
- Select 3 credit hours from the Explore - Arts, Humanities and Cultures List
- Select 3 credit hours from the Explore - Society, Behavior and Health list (maybe fulfilled by required BUSN/ECON course)
Communication Skills (6 Credit Hours)
Data Analytics and Systems Engineering Core (21 Credit Hours)
Technical Electives (9 Credit Hours)
9 credit hours must be completed. Sample topics are listed below. Courses must be 3000-level or higher unless approved by program director.
- Non-linear Programming
- Time Series
- Stochastics/Regression/Statistical Process Control options
- Database Management
- Supply Chain Management
- Other courses in Engineering, Business, and Psychology as approved by Program Director
Open Electives (5-14 Credit Hours)
Complete open electives to fulfill the total hours requirement for the degree program. The chosen course(s) can be selected from any discipline but may not include any math course below MATH 1350. Only 3 credit hours of CS coursework numbered below CS 1150 may count toward Electives. Some possible topics are listed below:
- Non-linear Programming
- Queuing
- Simulation
- Time Series
- Stochastics/Regression/Statistical Process Control options
Engineering Capstone (5 Credit Hours)
You must have senior level classification in order to take the capstone.
Sample Schedule
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Freshman Year
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Fall Semester (16 credit hours)
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Spring Semester (15 credit hours)
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Sophomore Year
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Fall Semester (17 credit hours)
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Spring Semester (16 credit hours)
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Junior Year
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Fall Semester (18 credit hours)
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Spring Semester (18 credit hours)
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- DASE 3400 Mathematical Modeling & Differential Equations
- DASE 4000 Intro to Operations Research
- DASE 4720 Design/Analysis of Algorithms
- DASE 4030 Intro to Systems Engineering
- Tech Elective #1
- Tech Elective #2
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- CS 4770 Data Visualization
- CS 4430 Data Mining
- DASE 4910 Design of Experiments
- MAE 3342 Engineering Economy
- Elective (Sustainability) #1
- Tech Elective #3
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Senior Year
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Fall Semester (15 credit hours)
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Spring Semester (15 credit hours)
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Total credit hours: 128
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Return to: Programs
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