Supervised practicum experiences related to the Professional preparation of Rehabilitation Counselors or Special Education Teachers, including practice in delivering lectures, conducting class discussions, leading seminars, directing independent studies, guiding student research projects, demonstrating instructional methods and materials, supervising rehabilitation counselors or special education student teachers, and advising. Laboratory, three-nine hours. May be repeated to a maximum of nine credits.

Supervised practicum experiences related to the Professional preparation of Rehabilitation Counselors or Special Education Teachers, including practice in delivering lectures, conducting class discussions, leading seminars, directing independent studies, guiding student research projects, demonstrating instructional methods and materials, supervising rehabilitation counselors or special education student teachers, and advising. Laboratory, three-nine hours. May be repeated to a maximum of nine credits.

An independent study supervised research course for advanced graduate students in Rehabilitation Counseling, Special Education, or Early Childhood with an interest in a specific research problem. Class hours determined with supervising instructor. Note: for Rehabilitation Counseling doctoral students this course will satisfy CACREP internship requirements in the Research core area. Additional internships in 2 additional core areas are also required.

An independent study supervised research course for advanced graduate students in Rehabilitation Counseling, Special Education, or Early Childhood with an interest in a specific research problem. Class hours determined with supervising instructor. Note: for Rehabilitation Counseling doctoral students this course will satisfy CACREP internship requirements in the Research core area. Additional internships in 2 additional core areas are also required.

An independent study supervised research course for advanced graduate students in Rehabilitation Counseling, Special Education, or Early Childhood with an interest in a specific research problem. Class hours determined with supervising instructor. Note: for Rehabilitation Counseling doctoral students this course will satisfy CACREP internship requirements in the Research core area. Additional internships in 2 additional core areas are also required.

An independent study supervised research course for advanced graduate students in Rehabilitation Counseling, Special Education, or Early Childhood with an interest in a specific research problem. Class hours determined with supervising instructor. Note: for Rehabilitation Counseling doctoral students this course will satisfy CACREP internship requirements in the Research core area. Additional internships in 2 additional core areas are also required.

This course is an opportunity for experimental, topical or interdisciplinary experience for up to 9 hours of credit without creating a permanent course. The description and course subtitle will be submitted each time the course is offered. Subtitle required.

This course is an opportunity for experimental, topical or interdisciplinary experience for up to 9 hours of credit without creating a permanent course. The description and course subtitle will be submitted each time the course is offered. Subtitle required.

This course will include two major parts: machine learning theories and applications. Machine learning theories will cover legacy techniques (e.g., support vector machine, Bayesian inference) and then go deeper into deep learning (convolutional and recurrent neural network). The application part will cover some practical studies on how can we leverage the machine learning techniques to analyze the data collected from factory floors. Also, programming of the machine learning techniques (e.g., Python) will be covered in the class as well.

A multidisciplinary approach combining engineering principles for systems analysis and control, knowledge of biological control mechanisms, and computational properties of biological neural networks in the development of engineering neural networks for control applications. Topics include: equivalent circuit models for biological neurons and networks, non-linear differential equation representations, biological control strategies for rhythmic movements, design and development of controller for robot function, proposal development and presentation.