Course content is variable and reflects the current trends in software engineering. Support for metrics. This course focuses on the engineering and analysis of network protocols and architecture in terms of the Internet. This course focuses on computational issues in the theory of games, economics, and network design. Undergraduate Bulletin. Topics include: Locomotion, Non-visual sensors and algorithms, Uncertainty modeling, data fusion, State space models, Kalman filtering, Visual sensor, Sampling theory, Image features, Depth reconstruction, Multiple view geometry, Ego-motion, Active vision, Reasoning, Spatial decomposition, Geometric representations, Topological representations, Path planning, Spatial uncertainty, Active control, Pose maintenance, Dead reckoning, Correlation-based localization, Sensorial maps, Task planning and task interference, Multi-agent coordination. Introduction to fundamental topics in computer vision and the application of statistical estimation techniques to this area. Design of efficient algorithms for a variety of problems, with mathematical proof of correctness and analysis of time and space requirements. Formal definition of syntax with emphasis on context-free languages. Topics include: Feature extraction, Probabilistic modeling, Camera calibration, Epipolar geometry, Statistical estimation, Model reconstruction, Statistical filtering, Motion estimation, Recognition, Shape from single image cues. Computational complexity topics such as time complexity, NP-completeness and intractability, time and space hierarchy theorems. The PDF will include all information unique to this page. We will examine how existing security mechanisms can be applied to the CPS system, why such protections are not enough, and study the trend of security system design in the area. A minimum of four courses are required for this specialization. The goal of this course is to help students develop a solid understanding of the fundamentals of security and become familiar with the theories of cryptography as well as the role of cryptography in the recent and emerging applications. Analytic and simulation techniques for the performance analysis of computer architecture, operating systems and communication networks. Of considerable interest to the computer science community are problems that arise from the Internet and computer networks and are similar to issues that arise in traditional transport networks, e.g. Investigation and discussion by faculty and students concentrated on some topic of current interest. Code-based testing. Prerequisite working knowledge of Matlab or C/C++ is necessary. Discourse. Advanced topics in compiler construction, including incremental and interactive compiling, error correction, code optimization, models of code generators, etc. Possible topics include active learning, reinforcement learning, online learning, non-parametric learning, inductive learning, statistical relational learning, dimensionality reduction, ensemble methods, transfer learning, outlier detection, specific application areas of machine learning, and other relevant and/or emerging topics. This course will discuss how we can enable humans and machine learning systems to interact and collaborate for more effective and accurate decision making. (Credit will not be given for CS 521 if CS751 is taken). The topics such as Summarization, cross-lingual, Meta-Search, Question Answering, Parallel and distributed IR systems are discussed. A combination of analytical and experimental analysis techniques will be used to study topics such as protocol delay, end-to-end network response time, intranet models, Internet traffic models, web services availability, and network management. This course will cover probabilistic graphical models -- powerful and interpretable models for reasoning under uncertainty. Presentation techniques from white board to web-based instructional units using currently available software. Instructor permission required. The course requires sufficient math and programming background but does not require prior knowledge in machine learning. This course will teach various modern topics in network and computer security. 1: CS 201 is a one-semester, accelerated course equivalent to the two-semester CS 115 / CS … New technologies have increasingly enabled corporations and governments to collect, analyze and share huge amount of data related to individuals. Also, quality of service issues in broadband networks and a view of the convergence of technologies in broadband networks are covered. Comprehensive coverage of the problems involved in database system implementation and an in-depth examination of contemporary structures and techniques used in modern database management systems. Reliability analysis. This is achieved through a series of individual programming and process projects. Provides supervised experience in the development of computer-based teaching units. Static and dynamic analysis. Purpose of the Illinois Institute of Technology Undergraduate Bulletin This bulletin describes the academic programs and resources, policies, procedures, and student services in effect at the time of publication. This includes fixed dimensional linear programming and shortest paths. Therefore, in the last part of the course we cover techniques for representing and keeping track of the origin and creation process of data (its provenance). This course introduces cellular/PCS systems, short-range mobile wireless systems, fixed wireless systems, satellites, and ad hoc wireless systems. Focus is on transaction management, database structures and distributed processing. The focus of this course is to discuss and understand the challenges in emerging cyber-physical systems and to explore possible solutions from the perspectives of systems specification, system modeling, programming languages, systems designs, and software engineering. It will provide a thorough grounding in cyber-security for students who are interested in conducting research on security and networking and for students who are more broadly interested in real-world security issues and techniques. These techniques integrate well with software process management techniques and provide a framework for software engineers to collaborate in the design and development process. Introduces the complexity classes P, NP, NL, L, PSPACE, NC, RNC, BPP and their complete problems. The thesis/project culminates in a presentation to a committee for approval in their last semester (six credit hours of CS 491 or CS 497). May be taken more than once. Key topics include, but are not limited to: Fundamentals of automated software testing, automated test design, modeling and generation, automated test execution, automated test management, automated test metrics, automated tools, automated feature and regression testing Environments to support cost-effective automated software testing, discussions on the barriers to industrial use of automated testing. The programs of study and requirements outlined in the 2017-2018 Undergraduate Bulletin apply to all students who entered IIT for the first time in the fall of 2017. CS 201 is a one-semester, accelerated course equivalent to the two-semester CS 115/CS 116 sequence. Deep networks are suitable for parallel processing implementations and can easily leverage intensive computational resources. telephone: 410.347.7700. This course provides an introduction to the theory of formal languages and machines. At least one course must be in a field other than physics.