Courses

Introduces practice and research in human-computer interaction, design of interactive systems, computer supported cooperative work, computer supported collaborative learning, educational technology, tools that support creativity, user-developed knowledge collections, and gaming.

Supports students in developing professional skills and practices in human-computer interaction, design of interactive systems, computer supported cooperative work, computer supported collaborative learning, educational technology, tools that support creativity, user-developed knowledge collections, and gaming. May be repeated up to 10 total credit hours. Same as ATLS 3112.

Surveys artificial intelligence techniques of search, knowledge representation and reasoning, probabilistic inference, machine learning, and natural language processing. Introduces artificial intelligence programming. Prerequisites: Requires pre-requisite course of CSCI 2824 (minimum grade C-).

Introduces students to fundamental concepts in autonomous, mobile robotics: mechanisms, locomotion, kinematics, control, perception and planning. The course consists of lectures and lab sessions that are geared toward developing a complex robot controller in a realistic, physics-based multi-robot simulator. Prereqs., CSCI 2270 and 2824. CSCI 3302 and ECEN 3303 are the same course.

Introduces cognitive science, drawing from psychology, philosophy, artificial intelligence, neuroscience, and linguistics. Studies the linguistic relativity hypothesis, consciousness, categorization, linguistic rules, the mind-body problems, nature versus nurture, conceptual structure and metaphor, logic/problem solving, and judgment. Emphasizes the nature, implications, and limitations of the computational model of mind. Prereqs., two of the following: PSYC 2145, LING 2000, CSCI 1300, and PHIL 2440. Same as LING 3005, PHIL 3310, and PSYC 3005.

Second course in artificial intelligence. Topics may vary, but typically cover neural networks, natural language processing, and artificial life. Prereq., CSCI 3202 or instructor consent.

Exposes students to current research topics in the field of robotics and provides hands-on experience in solving a grand challenge program. Prereq., CSCI 3302 or instructor consent required. Same as CSCI 5302.

Teaches students essential skills necessary for developing usable assistive and performance support systems, which include consideration of the academic and professional interdisciplinary issues that govern the work. An overview of ongoing and emerging topics in medical informatics will be presented. Prereq., CSCI 2270. Recommended prereq., CSCI 3002. Same as CSCI 5312.

Supports students in developing professional skills and knowledge concerning the use of computer technologies to support collaborative activities. Also covers the impact of digital collaboration technologies on users, groups, organizations and society. Students will gain practical experience with Business Process Management and the use of Workflow Management Systems. Same as CSCI 5342.

Explores the design of new media and technologies to support design and creativity. Analyzes design and creativity as human activities of fundamental importance in the networked information culture and economy. Provides theoretical and practical analysis of new media. Instructor consent required. Recommended prereq., CSCI 3002. Instructor consent required. Same as CSCI 5412.

Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to scalability and efficiency. Topics covered include data preprocessing, data warehouse, association, classification, clustering, and mining specific data types such as time-series, social networks, multimedia, and Web data. Prereq., CSCI 2270 or instructor consent. CSCI 4502 and 5502 are the same course.

Exposes students to current research topics in the field of robotics and provides hands-on experience in solving a grand challenge program. Prereq., CSCI 3302 or instructor consent required. Same as CSCI 4302.

Same as CSCI 4312. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Same as CSCI 4342. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Same as CSCI 4412. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to scalability and efficiency. Topics covered include data preprocessing, data warehouse, association, classification, clustering, and mining specific data types such as time-series, social networks, multimedia, and Web data. Prereq., CSCI 2270 or instructor consent. CSCI 4502 and 5502 are the same course. Prerequisites: Restricted to Graduate Students only.

Surveys artificial intelligence methods, theories, and applications. Studies the relationship between artificial intelligence and psychology, linguistics, and philosophy. Introduces artificial intelligence programming. Prereq., CSCI 3155 or equivalent. Same as ECEN 5583. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Trains students to build computer systems that learn from experience. Includes the three main subfields: supervised learning, reinforcement learning and unsupervised learning. Emphasizes practical and theoretical understanding of the most widely used algorithms (neural networks, decision trees, support vector machines, Q-learning). Covers connections to data mining and statistical modeling. A strong foundation in probability, statistics, multivariate calculus, and linear algebra is highly recommended. Prereq., graduate standing or instructor consent. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Explores algorithms that can extract information about the world from images or sequences of images. Topics covered include: imaging models and camera calibration, early vision (filters, edges, texture, stereo, optical flow), mid-level vision (segmentation, tracking), vision-based control, and object recognition. Recommended prereq., probability, multivariate calculus, and linear algebra. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Explores the field of natural language processing as it is concerned with the theoretical and practical issues that arise in getting computers to perform useful and interesting tasks with natural language. Covers the problems of understanding complex language phenomena and building practical programs. Prereq., graduate standing or instructor consent. Same as LING 5832. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree majors only.

Introduction to automatic speech recognition and understanding, conversational agents, dialogue systems, and speech synthesis/text-to-speech. Topics include the noisy channel model, Hidden Markov Models, A* and Viterbi decoding, language modeling (N-grams, entropy), concatenative synthesis, text normalization, dialogue and conversation modeling. Prereqs., CSCI 5582 or 5832, or LING 5200, and graduate standing or instructor consent. Prerequisites: Restricted to Graduate Students only.

Interdisciplinary introduction to cognitive science, examining ideas from cognitive psychology, philosophy, education, and linguistics via computational modeling and psychological experimentation. Includes philosophy of mind; learning; categorization; vision and mental imagery; consciousness; problem solving; decision making, and game-theory; language processing; connectionism. Prereqs., graduate standing, or at least one course at the 3000-level or higher in computer science, linguistics, philosophy, or psychology. No background in computer science will be presumed. Same as EDUC 6504, LING 6200, PHIL 6310, and PSYC 6200. Prerequisites: Restricted to Graduate Students only.

Covers advanced theoretical and practical topics in machine learning and latest developments in the field. Students conduct original research, either applied or theoretical, and present their results. Prereq., CSCI 5622 or instructor consent. Prerequisites: Restricted to Graduate Students only.

Topics vary from year to year. Possible topics include search; knowledge representation and natural language understanding; deduction, planning, problem solving, and automatic programming; instruction and cognitive models; vision and speech; and learning, induction, and concept formation. Prereq., CSCI 5582 or instructor consent. Prerequisites: Restricted to Graduate Students only.

Topics vary from year to year. Possible topics include human and machine vision, signal and speech processing, artificial life, mathematical foundations of connectionism, and computational learning theory. Prereq., CSCI 5622 or instructor consent. Prerequisites: Restricted to Graduate Students only.