4 courses with the subject DAEN, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DAEN 500Data Analytics Fundamentals3
Provides a foundation in data analytics from which the student will build. Focuses on a dataset where students will use analytics tools and apply statistical methodologies in order to extract information of value.Offered by Engineering & Computing. May not be repeated for credit.Registration Restrictions: Enrollment limited to students with a class of Advanced to Candidacy, Graduate, Junior Plus, Non-Degree or Senior Plus.
This is an introductory course in machine learning and pattern recognition that covers basic theory, algorithms, and applications. Machine learning is the science of getting computers to act without being explicitly programmed. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. It provides a broad introduction to machine learning and pattern recognition. Topics include: (i) supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, autoencoders). (iii) Learning theory (bias/variance tradeoffs, VC theory, generalization). (iv) Ensemble methods (boosting and bagging, random forests). (v) Deep learning (deep belief networks, convolutional neural networks, deep autoencoders). The course will draw from numerous case studies and applications.Offered by Engineering & Computing. May not be repeated for credit. Equivalent to ECE 527.Recommended Prerequisite: (MATH 203 and STAT 346) or equivalentRegistration Restrictions: Enrollment limited to students with a class of Advanced to Candidacy, Graduate, Junior Plus, Non-Degree or Senior Plus.
Capstone project course for MS in Data Analytics program. Key activity is completion of a major applied team project resulting in an acceptable technical report and oral briefing. Students should plan to take this academically rigorous course in their last semester.Offered by Engineering & Computing. May not be repeated for credit.Recommended Prerequisite: Completion of 21 credit hours of coursework in the MS Data Analytics program and departmental approval to register. It is also recommended that DAEN 690 be taken in your last semester and with no more than one other course at the same time.Registration Restrictions: Enrollment limited to students with a class of Advanced to Candidacy, Graduate, Junior Plus, Non-Degree or Senior Plus.
Conduct a research project to be chosen and completed under guidance of a graduate faculty member that results in an acceptable technical report. Notes: No more than a total of three credits may be taken from within the DAEN program.Offered by Engineering & Computing. May be repeated within the term for a maximum 3 credits.Specialized Designation: Topic VariesRecommended Prerequisite: Graduate Standing, completion of at least two core courses and a minimum of 12 credits in the DAEN program, and permission of instructor.Registration Restrictions: Enrollment limited to students with a class of Advanced to Candidacy, Graduate, Junior Plus, Non-Degree or Senior Plus.
Subject
DAEN
Credits (min)
1
Credits (max)
3
Credit unit
credits
Type
course
Repeatable
May be repeated within the term for a maximum 3 credits.
