FALL 2020 SCHEDULE
|
Course
|
Course Title
|
Faculty
|
Time
|
Bldg/Room
|
|
COT5570
|
Introductory Math for Modeling and Simulation
|
Li, Yao
|
T, Th 3:00 PM - 04:15 PM
|
Partnership 3 Room 233
|
|
IDC5602
|
Cybersecurity: A Multidisciplinary Approach
|
Caulkins, Bruce
|
W 5:00 PM - 7:50 PM
|
Partnership 3 Room 233
|
|
IDC6941
|
Capstone for Behavioral Cybersecurity
|
Caulkins, Bruce
|
T 5:00 PM - 7:50 PM
|
Partnership 3 Room 233
|
|
IDS6145
|
Simulation Techniques
|
Kider, Joe
|
M, W 3:00 PM - 4:15 PM
|
Partnership 3 Room 233
|
|
IDS6147
|
Perspectives on Modeling and Simulation
|
Bockelman, Patricia
|
M 6:00 PM - 8:50 PM
|
Partnership 3 Room 233
|
|
IDS6262
|
Research Design for Modeling and Simulation
|
Amon, Mary Jean
|
T 3:00 PM - 5:50 PM
|
Partnership 2 Room 141
|
|
IDS6916
|
Simulation Research and Practicum
|
Kider, Joe
|
W 5:00 PM - 6:50 PM
|
Partnership 3 Room 113
|
|
IDS6938
|
ST: Modeling Neuronal Systems
|
Douglas, Pamela
|
W 2:00 PM - 4:50 PM
|
Partnership 2 Room 141
|
PROGRAM COURSES
COT 5570 - Introductory Mathematics for Modeling and Simulation
A preparatory analytical survey of material for the M&S core Math Foundations course: algebra, discrete mathematics, and basic probability.
Last taught: Fall 2020
Syllabus
COT 6571 - Mathematical Foundations of Modeling & Simulation
We will emphasize critical thinking and problem-solving skills as we conduct a high-level survey of traditional topics in probability & statistics, linear algebra, and calculus. Students will be expected to practice and solve both basic structured mathematical problems, as well as “puzzles” designed to place quantitative topics in a deeper context.
Last taught: Spring 2020
Syllabus
IDC 5602 - Cybersecurity: A Multidisciplinary Approach
IDC 5602 consists of modeling and simulation fundamentals as applied to cybersecurity including operating system installation and administration for hardware, network architectures, layers, protocols, and configurations. Cyber threats and vulnerabilities are discussed, as well as the behavioral aspects of cybersecurity. Valid cyber training and education models are explored. Modeling and simulation concepts are discussed as complements to activities supporting cybersecurity in small and large organizations.
Last taught: Fall 2020
Syllabus
IDC 6941 - Capstone in Modeling and Simulation of Behavioral Cybersecurity
This is the capstone course for the Graduate Certificate in Modeling and Simulation of Behavioral Cybersecurity. In this course, you will be walking through the research process by working through stages from design to dissemination in a manner that works to replicate much of what we do in Modeling, Simulation, & Training (MS&T) research. IDC 6941 also focuses on human, social, and behavioral issues related to cybersecurity including organizational management techniques, motives for cybercrimes, risk and threat analysis, and ethics and legal issues. Top modeling and simulation techniques and some relevant psychological issues including human systems integration and human-computer interaction will be applied as they relate to securing data, computers, and the networks on which these reside.
Last taught: Fall 2020
Syllabus
IDS 6145 - Simulation Techniques (*Department consent required*)
This course provides a broad survey of three different categories of simulation techniques: continuous simulation, discrete event simulation, and agent-based simulation. The material in this course will provide an overview of the foundations as well as specific example problems and simulation solutions for each category of simulation. Students will be expected to understand the basics for a variety of different types of simulations, as well as to work with hands-on simulation tools to implement solutions to various problems.
Last taught: Fall 2020
Syllabus
IDS 6147 - Perspectives of Modeling and Simulation
This is a mixed-mode/ reduced seat time course designed to introduce students to academic work in M&S at the graduate level. It is a core course for the M&S graduate programs, although we have many students from other UCF programs. By the end of the course, students will be aware of interdisciplinary challenges and opportunities facing this diverse field. Students will demonstrate familiarity with a range of topics and professional track options, with an emphasis on the resources available in the central Florida research corridor. Students will demonstrate academic written and oral communication skills. It is the goal of this class to bridge undergraduate knowledge and graduate-level rigor.
Last taught: Fall 2020
Syllabus
IDS 6148 - Human-Systems Integration in Modeling and Simulation
This course will introduce students to a systems engineering mindset, and it will directly explore issues related to the planning, design, and evaluation of HSI engineering efforts. These include principles of the primary HSI domains (manpower, personnel, training, human factors, habitability, safety, and survivability), as well as related topics, such as HSI leadership, storytelling, and political/cultural issues. Evaluation techniques will also be emphasized, and the course will include a variety of analyses approaches that help HSI practitioners forecast downstream outcomes, reduce risk, manage costs, and improve system(s) performance. Finally, the course will include discussion about how each of these techniques can support the development of Modeling, Simulation, and Training (MS&T) systems as well as how M&S can support the execution of HSI tasks.
Last taught: Spring 2020
Syllabus
IDS 6262 - Research Design for Modeling and Simulation
This course provides an overview of modeling and simulation research techniques, intending to support the development of human-subject research skills and ethical conduct in research. This is a core course for graduate students in the School of Modeling, Simulation, and Training, though it is open to students from other disciplines.
Last taught: Fall 2020
Syllabus
IDS 6267: Understanding Humans for Modeling and Simulation
The purpose of this course is to introduce Modeling and Simulation graduate students how the human mind and body work with interactive, “human in the loop” simulations. The course will provide a better understanding of human cognition, the human perceptual system, ergonomics, and how humans and computing systems can connect through the process of user-centered design and analysis.
Last taught: Spring 2020
Syllabus
IDS6916 - Research Design and Practicum
This is a project course that is included in the core for M.S. (and Ph.D.) students in Modeling and Simulation (M&S). It serves as a capstone course for M.S. students in M&S. Interdisciplinary teams of students conduct fundamental and applied research on contemporary issues in modeling, simulation, and training. The material in this course will provide an overview of the foundations of Research Design and provide a practical project with a small team.
Last taught: Fall 2020
Syllabus
IDS 6938 - Special Topics Courses (offered occasionally)
ST: Modeling Neuronal Systems
This course first provides an overview of key concepts in neuroscience taking a bottom-up approach starting with microscopic and moving through mesoscopic and systems-level computing in the human
brain. We will cover key methods for measuring functional and dynamic activity in the human brain noninvasively (e.g., EEG, fMRI). Recently, deep learning neural networks have become an indispensable tool for brain computational modeling. We will then cover the foundations of deep learning and active inference models while examining the key parallels between artificial & biological neural networks.
Last taught: Fall 2020
Syllabus
ST: Nonlinear Dynamics in the Cognitive & Behavioral Sciences
This course provides an introductory overview of nonlinear dynamical modeling and simulation research techniques, which are especially well-suited for understanding temporal (i.e., time series) or structural data. The first half of the course presents theory relevant to understanding complex systems, and the second half introduces nonlinear and dynamical analytic techniques such as entropy, fractal, recurrence, and wavelet.
Last taught: Spring 2020
Syllabus
ST: Usable Security & Privacy
The course introduces usability problems in security and privacy methods, tools, and software and overviews prominent examples of both failures and successes in usable security and privacy. It also surveys state-of-the-art techniques and evaluation methodologies. Students will learn different methods for usability tests in security and privacy design. They will practice the usability tests through a term project, including actually recruiting participants, collecting data, evaluating the usability, presenting the test results in oral and written form.
Last taught: Fall 2020
Syllabus