Special topics courses provide an opportunity for in-depth study of topics not offered elsewhere and of topics of current significance.
- CIS4930 for undergraduate students
- CIS6930 for graduate students
Brief descriptions and expected prerequisites can be found below.
CIS4930 Internet Computing (undergrad only)
Instructor: Albert D. Ritzhaupt
Expected background: COP3503
CIS4930 Mathematics for Machine Learning (undergrad only)
Instructor: Kejun Huang
Expected background: Calculus and Linear Algebra
Description: Modern machine learning can be demanding due to its reliance on a set of interlocking applied math concepts. In this course (assuming a background in linear algebra and calculus), we begin with vector spaces, bases and dimension and then gently introduce the topics of linear regression, objective functions for optimization, maximum likelihood and entropy, and the essentials of constrained optimization and Lagrange parameters – all necessary tools of machine learning.
CIS6930 Expressive Agents (grad only)
Instructor: Eakta Jain
Description: Humans increasingly interact with physical and virtual agents in all areas of life and work. This course will cover foundational concepts and currently ongoing work in the multidisciplinary pursuit of generating expressive agents. Students will get an overview of the field and experience first-hand the challenges involved through project activities. At the end of this course, students will be able to locate literature relevant to their interest, analyze research papers, demonstrate critical thinking and effective technical communication, and translate scientific reports into practical implementations.
CIS4930 Enterprise Software Engineering Practices (undergrad only)
Instructor: David Wright
Expected background: recommend CEN3031: Intro to Software Engineering
Description: Do you aspire to work in the tech industry? Do you want to learn how software gets built in large, billion-dollar companies? Do you want to stand out among other intern and full-time candidates? This course will be taught by industry leaders and former UF CISE graduates who have put together 100% of the content based on real-world experiences building enterprise software. The course will cover: processes, frameworks, and tools that large companies use to allow hundreds of engineers to collaborate and deliver software; how technology teams interface with other business units to deliver products and solutions; and modern software engineering best practices and enterprise architecture patterns.
CIS4930/CIS6930 Computer Security and Privacy for Marginalized and Vulnerable Populations (co-taught undergrad and grad sections)
Instructor: Kevin Butler
Expected background: Some background in computer security and privacy (e.g. a graduate or undergraduate course in security) would be helpful but is not required. An understanding of research methods for human-centered computing research would also be helpful but is not required.
Description: Computing has never been more important to our daily lives than in the current moment. The COVID-19 pandemic was a watershed moment for how we interact with others, demonstrating how technology could mediate all communication. Many other disruptive yet innovative technologies are on the horizon such as mixed reality and more pervasive integrated technology in our physical environments, such as sensors within smart cities. However, one constant throughout this rapid evolution in computing is that the needs of marginalized and vulnerable (M&V) populations have been under-addressed, as have the consequences of their exclusion. This course will examine how computer security and privacy research with M&V populations has occurred in the past, attempt to systematize lessons learned, and provide research opportunities for future work in this area. Students will gain exposure to foundational and cutting-edge research in computer security and privacy as well as human-centered research techniques, and gain an understanding of how computing can both uplift and disempower vulnerable groups depending on how it is deployed.
CIS4930 Internet Networking Technologies (undergrad only)
Instructor: Jonathan Kavalan
Description: Design and analysis of Internet networking technologies from application’s point of view. Major effort is devoted on application natures, and their impact on high-level protocols at the application- and transport-layer
CIS6930 Data Engineering (grad only)
Instructor: Christian Grant
Description: Data are the fundamental units in Artificial Intelligence (AI) and Machine Learning (ML) systems. Effectively harnessing this data is the responsibility of software engineers and data scientists. In this course, we will survey the landscape of AI/ML systems to understand how data flows through the systems. We will look at the engineer’s responsibilities for developing performant systems ethically and responsibly. Students will learn how to design, build, and evaluate data pipelines. We will cover the theoretical underpinnings of fairness and bias throughout data systems. Students will produce a comprehensive project using state-of-the-art systems that integrate best practices.
CIS4930/CIS6930 3D Audio (co-taught undergrad and grad sections)
Instructor: Kyla McMullen
Description: Students will understand the role of audio in human-computer interaction, the physiological and computational aspects of rendering accurate spatial audio, the tradeoffs when designing 3D audio applications. Students will develop a 3D audio system, learn, and discuss research trends, and hone presentation and writing skills, as evidenced through project milestones.