PROGRAM INFORMATION

The Master of Science with a major in Applied Data Science degree will provide students with a working knowledge of techniques and software commonly used in Data Science. The degree is designed for engineering students and working professional engineers with a B.S. degree in a non-computing engineering field, that is, for engineering students and professional engineers who have engineering degrees other than Computer Science or Computer Engineering and possibly Industrial and Systems Engineering. The degree will prepare engineering students to work as data scientists in industry and can also be used by engineering students working towards a Ph.D. degree in non-computing focused engineering degree programs.  

DEGREES OFFERED WITH A MAJOR IN applied data science

  • Master of Science

applied data SCIENCE PROGRAM COURSES

Core/Required Courses:

CAP 5771Introduction to Data Science3
COT 5615Mathematics for Intelligent Systems3
EEE 5776Applied Machine Learning3
EEE 6778Applied Machine Learning II3
EGN 6446Mathematical Foundations for Applied Data Science3
EGN 5442Programming for Applied Data Science3
EGN 6933Special Topics1-3
LAW 6930Selected Legal Probs1-4

Example Specialization Courses

ABE 5038Recent Developments and Applications in Biosensors3
ABE 5643CBiological Systems Modeling3
ABE 6035Advanced Remote Sensing: Science and Sensors3
ABE 6649CAdvanced Biological Systems Modeling3
ABE 6840Data Diagnostics3
BME 6522Biomedical Multivariate Signal Processing3
BME 6938Special Topics in Biomedical Engineering1-4
BME 6938Special Topics in Biomedical Engineering1-4
EIN 6905Special Problems1-6
OCP 6168Data Analysis Techniques for Coastal and Ocean Engineers3
TTE 6505Discrete Choice Analysis3

ENGINEERING EDUCATION departmental COURSES

College of Engineering Courses

EEE 5354LSemiconductor Device Fabrication Laboratory3
EEE 5776Applied Machine Learning3
EEE 6778Applied Machine Learning II3
EGN 5215Machine Learning Applications in Civil Engineering3
EGN 5216Machine Learning for Artificial Intelligence Systems3
EGN 5442Programming for Applied Data Science3
EGN 6216Artificial Intelligence Systems3
EGN 6217Applied Deep Learning3
EGN 6446Mathematical Foundations for Applied Data Science3
EGN 6640Entrepreneurship for Engineers3
EGN 6642Engineering Innovation3
EGN 6913Engineering Graduate Research0-3
EGN 6933Special Topics1-3
EGN 6937Engineering Fellowship Preparation0-1
EGS 6012Research Methods in Engineering Education3
EGS 6020Research Design in Engineering Education3
EGS 6039Engineering Leadership3
EGS 6050Foundations in Engineering Education3
EGS 6051Instructional Design in Engineering Education3
EGS 6054Cognition, Learning, and Pedagogy in Engineering Education3
EGS 6056Learning and Teaching in Engineering1
EGS 6085Advanced Engineering Educational Technology3
EGS 6101Divergent Thinking3
EGS 6626Fundamentals of Engineering Project Management3
EGS 6628Advanced Practices in Engineering Project Management3
EGS 6629Agile Project Management for Engineers and Scientists3
EGS 6681Advanced Engineering Leadership3
EGS 6930Engineering Education Seminar1
EGS 6940Preparation for Engineering Education Practicum1
EGS 6949Research to Practice Experience in Engineering Education1-3
EGS 6971Research for Master’s Thesis1-12
EGS 7979Advanced Research1-12
EGS 7980Research for Doctoral Dissertation1-12
ESI 6900Principles of Engineering Practice1-4

Applied data SCIENCE

SLO 1     Knowledge        
To analyze, design, implement, and evaluate Data Science systems solution to meet a given set of system requirements. 

SLO 2     Skills     
To recognize professional responsibilities and make informed decisions when developing Data Science systems based on legal, ethical, and policy principles.

SLO 3     Professional Behavior   
To function effectively as a member of a team engaged to develop a Data Science systems solution.