CS 498

Fall 2019 All Classes

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Credit: 0 TO 4 hours.

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.

1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

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CS 498 class schedule data for fall 2019
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
68911	Lecture	AM3	11:00AM -12:20PM	TR	2013 Electrical & Computer Eng Bldg	Miller, A	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Applied Cryptography Restriction(s): Not intended for First Time Freshman students.
68912	Lecture	AM4	11:00AM -12:20PM	TR	2013 Electrical & Computer Eng Bldg	Miller, A	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Applied Cryptography Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.
43753	Lecture	CD	11:00AM -12:15PM	TR	1103 Siebel Center for Comp Sci	Gunter, C	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Cyber Dystopia Section Info: Section Info: Analyzing the Adverse Impacts of Advances in Computer Technology. The information revolution is bringing changes that are not always seen as positive to the people they affect. Nevertheless there is a strong feeling that the changes it brings are inevitable and that our efforts should be devoted to advancing, enjoying, and profiting from cyber technologies rather than restraining them. But do our efforts in this direction risk the emergence of a cyber dystopia in which many, perhaps most, people are significantly harmed by technology advances? This course focuses on insights into the downsides of this technological progress. We will characterize key aspects of the problem, assess their severity, predict their future, speculate on how much of what we are facing is inevitable, and think about what steps might avoid the most undesirable outcomes. This will be guided by reading and class discussion of recent works on the topic and a project. Learn more from the course web site https://tinyurl.com/cyberdystopia. Restricted to Undergrad - Urbana-Champaign, of their senior year Restriction(s): Not intended for First Time Freshman students.
70961	Online	CNO	ARRANGED	n.a.	n.a.	Godfrey, P	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Cloud Networking Section Info: Course description: Computer communication networks are among the most important and influential global infrastructures that humanity has created. The goal of this course is to provide a foundational view of communication networks, with a focus on networks enabling modern hyperscale cloud computing. In the first part of this course, we’ll study the principles upon which the Internet and other computer networks are built, and how those principles translate into deployed protocols. In the second part of this course, we build on those principles to learn how to build a network infrastructure that provides the agility to deploy virtual networks on a shared infrastructure, that enables both efficient transfer of big data and low latency communication, and that enables applications to be federated across countries and continents. Topics will include: switching; intradomain routing; the Internet Protocol and interdomain networking; reliability, flow control, congestion control, and their embodiment in TCP; quality of service; network applications; cloud network requirements and traffic patterns; data center network architecture; virtualized and software-defined networks; and wide-area connectivity. The course will involve a significant amount of Unix-based network programming and assumes some familiarity with C or C++. One shorter programming project employs Python. Students will implement realistic network protocols, and gain the perspective of real-world networking challenges through interviews with industry professionals and academic researchers. This course is only for students that are in the online Computer Science MCS/MCS-DS Program. Additional ProctorU fees may apply. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC. Not intended for First Time Freshman students.
66333	Lecture-Discussion	HS3	11:00AM -12:15PM	WF	1310 Digital Computer Laboratory	Sundaram, H	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Computational Advertising Section Info: This class will survey the emerging landscape of computational advertising. It will provide students with a thorough understanding of the technologies including web-search, auctions, behavioral targeting, mechanisms for viral marketing, that underpin the display of advertisements on a variety of locations. These locations include web pages (banner ads), on prominent search engines (text ads), on social media platforms, as well as cell phones. The students shall also learn about new research areas in computational advertising including electronic billboards, moving objects (banners atop taxi cabs) and algorithmic synthesis of personalized advertisements. This class will also discuss issues related to consumer privacy. Restriction(s): Not intended for First Time Freshman students.
66399	Lecture-Discussion	HS4	11:00AM -12:15PM	WF	1310 Digital Computer Laboratory	Sundaram, H	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Computational Advertising Section Info: This class will survey the emerging landscape of computational advertising. It will provide students with a thorough understanding of the technologies including web-search, auctions, behavioral targeting, mechanisms for viral marketing, that underpin the display of advertisements on a variety of locations. These locations include web pages (banner ads), on prominent search engines (text ads), on social media platforms, as well as cell phones. The students shall also learn about new research areas in computational advertising including electronic billboards, moving objects (banners atop taxi cabs) and algorithmic synthesis of personalized advertisements. This class will also discuss issues related to consumer privacy. Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.
72154	Lecture-Discussion	IT3	9:30AM -10:45AM	MW	0216 Siebel Center for Comp Sci	Caesar, M	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Internet of Things Restriction(s): Not intended for First Time Freshman students.
72155	Lecture-Discussion	IT4	9:30AM -10:45AM	MW	0216 Siebel Center for Comp Sci	Caesar, M	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Internet of Things Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.
72360	Online	ITC	ARRANGED	n.a.	n.a.	Caesar, M	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Internet of Things Section Info: This course includes in-person activities such as discussions, reviews or exams in Chicago. Restriction(s): Restricted to O/C Engineering City Scholars students.
42449	Online	ITO	ARRANGED	n.a.	n.a.	Caesar, M	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Internet of Things Section Info: The Internet of Things (IoT) stands to be the next revolution in computing. Billions of data-spouting devices connected to the Internet are already fundamentally changing the way we live and work. This course teaches a deep understanding of IoT technologies from the ground up. Students will learn IoT device programming (Arduino and Raspberry Pi), sensing and actuating technologies, IoT protocol stacks (Zigbee, 5G, NFC, MQTT, etc), networking backhaul design and security enforcement, data science for IoT, and cloud-based IoT platforms such as AWS IoT. Students will be guided through laboratory assignments designed to give them practical real-world experience, where they will deploy a distributed wifi monitoring service, a cloud-based IoT service platform serving tens of thousands of heartbeat sensors, and more. Students will emerge from the class with a cutting-edge education on this rapidly emerging technology segment, and with the confidence to carry out tasks they will commonly encounter in industrial settings. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC.
71011	Online	MCO	ARRANGED	n.a.	n.a.	Godfrey, P	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Cloud Networking Section Info: Additional Coursera ID verification and ProctorU fees may apply Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to MCS:Computer Sci Online -UIUC. Not intended for First Time Freshman students.
72152	Lecture-Discussion	RA3	2:00PM -3:15PM	TR	1103 Siebel Center for Comp Sci	Har-Peled, S	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Intro to Randomized Algs Section Info: Randomness has proven itself to be a useful resource for developing provably efficient algorithms and protocols. As a result, the study of randomized algorithms has become a major research topic in recent years. This course will explore techniques for effectively using randomization and for analyzing randomized algorithms, as well as examples from a variety of settings and problem areas. Topics covered would include basic probability, hashing, sampling, concentration inequalities (Chernoff), random processes (random walk, Markov chains, etc), learning, streaming, dimension reduction, and locality sensitive hashing. Algorithms for handling big data using these techniques would also be covered extensively. Restriction(s): Not intended for First Time Freshman students.
72153	Lecture-Discussion	RA4	2:00PM -3:15PM	TR	1103 Siebel Center for Comp Sci	Har-Peled, S	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Intro to Randomized Algs Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.
71965	Lecture-Discussion	RL3	2:00PM -3:15PM	TR	0216 Siebel Center for Comp Sci	Jiang, N	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Reinforcement Learning Section Info: Reinforcement learning (RL) is a machine learning paradigm for sequential decision-making, which has enabled the recent successes in video/board game playing (e.g., AlphaGo). In this course we will introduce the fundamental concepts and some basic algorithms for RL. Most of the course will be highly mathematical, and the goal is to enable students to (1) understand the mathematical framework of RL, (2) tell what problems can be solved with RL, and how to express these problems using the RL formulation, (3) understand why and how RL algorithms are designed to work in theory, and (4) know how to experimentally and mathematically evaluate the effectiveness of an RL algorithm. There will be both programming and written assignments. Prerequisites: Required: Linear algebra (Math 415 or equivalent), Probability and Statistics (CS 361 or equivalent). Recommended: Numerical methods (CS 357 or 450), AI or Machine Learning (CS 440 and/or 446). Restriction(s): Restricted to Undergrad - Urbana-Champaign. Not intended for First Time Freshman students.
71966	Lecture-Discussion	RL4	2:00PM -3:15PM	TR	0216 Siebel Center for Comp Sci	Jiang, N	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Reinforcement Learning Section Info: Reinforcement learning (RL) is a machine learning paradigm for sequential decision-making, which has enabled the recent successes in video/board game playing (e.g., AlphaGo). In this course we will introduce the fundamental concepts and some basic algorithms for RL. Most of the course will be highly mathematical, and the goal is to enable students to (1) understand the mathematical framework of RL, (2) tell what problems can be solved with RL, and how to express these problems using the RL formulation, (3) understand why and how RL algorithms are designed to work in theory, and (4) know how to experimentally and mathematically evaluate the effectiveness of an RL algorithm. There will be both programming and written assignments. Prerequisites: Required: Linear algebra (Math 415 or equivalent), Probability and Statistics (CS 361 or equivalent). Recommended: Numerical methods (CS 357 or 450), AI or Machine Learning (CS 440 and/or 446). Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.
40091	Lecture	VR3	2:00PM -3:15PM	MW	1404 Siebel Center for Comp Sci	Shaffer, E	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Virtual Reality Section Info: Fundamentals of virtual reality systems, including geometric modeling, transformations, graphical rendering, optics, the human vision system, the vestibular system, interface design, human factors, developer recommendations, and technological issues. Implementation exercises and a final project are included. Extensive programming background not required Restriction(s): Not intended for First Time Freshman students.
40092	Lecture-Discussion	VR4	2:00PM -3:15PM	MW	1404 Siebel Center for Comp Sci	Shaffer, E	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Virtual Reality Section Info: Fundamentals of virtual reality systems, including geometric modeling, transformations, graphical rendering, optics, the human vision system, the vestibular system, interface design, human factors, developer recommendations, and technological issues. Implementation exercises and a final project are included. Extensive programming background not required Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.
67900	Lecture	WN3	9:30AM -10:45AM	TR	1302 Siebel Center for Comp Sci	Kravets, R	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 3 hours Section Title: Wireless IoT Lab Section Info: Wireless networks are everywhere in our world, one laptops, smartphones, sensor and the new IoT devices popping up everywhere. Understanding how wireless networks work and why they break is the key to their successful deployment and integration. In the first half of this class, we focus on the basics of wireless networking, from the physical transmission of radio signals to the impact of lossy communication on higher layer routing and transport protocols. The second half of the class is dedicated to student let topics, including sensor networks, IoT, security and privacy, energy conservation and general performance improving techniques. Over the course of the semester, students design and implement a group project using a variety of wireless devices and technologies, ending with a project report and a poster presentation of their work. Restriction(s): Not intended for First Time Freshman students.
67901	Lecture	WN4	9:30AM -10:45AM	TR	1302 Siebel Center for Comp Sci	Kravets, R	Part of Term: 1 Date Range: 08/26/19-12/11/19 Credit: 4 hours Section Title: Wireless IoT Lab Section Info: Wireless networks are everywhere in our world, one laptops, smartphones, sensor and the new IoT devices popping up everywhere. Understanding how wireless networks work and why they break is the key to their successful deployment and integration. In the first half of this class, we focus on the basics of wireless networking, from the physical transmission of radio signals to the impact of lossy communication on higher layer routing and transport protocols. The second half of the class is dedicated to student let topics, including sensor networks, IoT, security and privacy, energy conservation and general performance improving techniques. Over the course of the semester, students design and implement a group project using a variety of wireless devices and technologies, ending with a project report and a poster presentation of their work. Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for First Time Freshman students.