CS 498

Fall 2020 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 2020
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
63294	Online	ABD	9:30AM -10:45AM	TR	n.a.	Chekuri, C Torres, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Algorithms for Big Data Section Info: Entirely online with some mix of asynchronous and synchronous components that may vary over the semester and based on needs of students and instructor. This course will describe some algorithmic techniques that have been developed for handling large amounts of data which may not fit in memory or is available in limited ways. Topics include data stream algorithms, sampling and sketching techniques, sparsification methods, and parallelization with applications to signals, matrices, and graphs. Emphasis will be on theoretical aspects of the design and analysis of such algorithms. Strongly suggested Prerequisites: grades of at least B+ in CS 374 and CS 361, or comparable understanding and facility with algorithms and probability. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister
63295	Online	ABG	9:30AM -10:45AM	TR	n.a.	Chekuri, C Torres, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Algorithms for Big Data Section Info: Entirely online with some mix of asynchronous and synchronous components that may vary over the semester and based on needs of students and instructor. This course will describe some algorithmic techniques that have been developed for handling large amounts of data which may not fit in memory or is available in limited ways. Topics include data stream algorithms, sampling and sketching techniques, sparsification methods, and parallelization with applications to signals, matrices, and graphs. Emphasis will be on theoretical aspects of the design and analysis of such algorithms. Strongly suggested Prerequisites: grades of at least B+ in CS 374 and CS 361, or comparable understanding and facility with algorithms and probability. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
68911	Online	AC3	11:00AM -12:20PM	TR	n.a.	Khurana, D	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Applied Cryptography Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister
68912	Online	AC4	11:00AM -12:15PM	TR	n.a.	Khurana, D	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Applied Cryptography Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
70185	Online	AML	ARRANGED	n.a.	n.a.	Delgosha, P Morales Aguirre, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Applied Machine Learning Section Info: This course will be taught on the Coursera platform. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. Description: The course is intended to support students who wish to apply machine learning methods, and will focus on tool-oriented and problem-oriented exposition. Application areas include computer vision, natural language, interpreting accelerometer data, and understanding audio data. Restriction(s): Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
69283	Online	AMO	ARRANGED	n.a.	n.a.	Delgosha, P Morales Aguirre, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Applied Machine Learning Section Info: This course is only for students that are in the Computer Science MCS-DS Program. Additional ProctorU fees may apply. Description: The course is intended to support students who wish to apply machine learning methods, and will focus on tool-oriented and problem-oriented exposition. Application areas include computer vision, natural language, interpreting accelerometer data, and understanding audio data. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
43753	Online	CD	11:00AM -12:15PM	TR	n.a.	Gunter, C	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Cyber Dystopia Section Info: All class meetings will be online and synchronous. 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 For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Undergrad - Urbana-Champaign. Not intended for First Time Freshman students.
64645	Online	CN1	ARRANGED	n.a.	n.a.	Godfrey, P	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Cloud Networking Section Info: This course will be taught on the Coursera platform. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. 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. (The material in this first part overlaps with CS 438.) 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. Credit will not be given for both CS 438 and CS 498 CN1. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister 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. Credit will not be given for both CS 438 and CS 498 CN1.
64649	Online	CN2	ARRANGED	n.a.	n.a.	Godfrey, P	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Cloud Networking Section Info: This course will be taught on the Coursera platform. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. 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. Credit will not be given for both CS 438 and CS 498 CN2. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
70961	Online	CNO	ARRANGED	n.a.	n.a.	Godfrey, P	Part of Term: 1 Date Range: 08/24/20-12/09/20 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. Credit will not be given for both CS 438 and CS 498 CNO. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
70363	Online	DL3	3:30PM -4:45PM	WF	n.a.	Lazebnik, S	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Introduction to Deep Learning Section Info: All class meetings will be online and synchronous. This course will provide an elementary hands-on introduction to neural networks and deep learning. Topics covered will include linear classifiers, multi-layer neural networks, back-propagation and stochastic gradient descent, convolutional neural networks, recurrent neural networks, generative networks, and deep reinforcement learning. Coursework will consist of programming assignments in TensorFlow or PyTorch. Those registered for 4 credit hours will have to complete a project. Prerequisites: multi-variable calculus, linear algebra, CS 361 or STAT 400. No previous exposure to machine learning is required. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister
70372	Online	DL4	3:30PM -4:45PM	WF	n.a.	Lazebnik, S	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Introduction to Deep Learning Section Info: All class meetings will be online and synchronous. This course will provide an elementary hands-on introduction to neural networks and deep learning. Topics covered will include linear classifiers, multi-layer neural networks, back-propagation and stochastic gradient descent, convolutional neural networks, recurrent neural networks, generative networks, and deep reinforcement learning. Coursework will consist of programming assignments in TensorFlow or PyTorch. Those registered for 4 credit hours will have to complete a project. Prerequisites: multi-variable calculus, linear algebra, CS 361 or STAT 400. No previous exposure to machine learning is required. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
58241	Online	FCS	12:30PM -1:45PM	TR	n.a.	Williams, T	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Fundamentals of Comp Sci I Section Info: Introduction to the concepts and craft of computer science. It teaches students to both think and act like computer scientists. It changes how they approach problems and provide them with powerful tools that they can use to change the world. The course assumes no prior programming experience. This course is restricted to students in the iCAN program. Restriction(s): Restricted to NDEG:Computer Science -UIUC.
43368	Online	FOA	2:00PM -3:15PM	TR	n.a.	Gertner, Y	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Fundamentals of Algorithms Section Info: Introduction to select topics of discrete mathematical frequently encountered in the study of Computer Science: counting, graphs, sets, functions, basics proofs, number theory, computability and introduction to algorithms. This class focuses on using these to model real world problems and utilize these techniques for problem solving. This course is restricted to students in the iCAN program. Restriction(s): Restricted to NDEG:Computer Science -UIUC.
64650	Online	HS1	12:30PM -1:45PM	WF	n.a.	Sundaram, H	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Social & Information Networks Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. Topic: Networks are to be found everywhere: from your familiar social networks to buyer-seller markets to protein-protein interactions. This class is an introduction to network science and we shall cover a broad range of concepts including: random graphs; networks and social contexts, networks and game theory, information diffusion and community detection. We shall discuss both classic questions about networks (how to model the spread of disease, what kinds of networks support decentralized search?) as well as more recent questions on networks with attributes and how to analyze massive networks efficiently. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister
64642	Online	HS2	12:30PM -1:45PM	WF	n.a.	Sundaram, H	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Social & Information Networks Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. Topic: Networks are to be found everywhere: from your familiar social networks to buyer-seller markets to protein-protein interactions. This class is an introduction to network science and we shall cover a broad range of concepts including: random graphs; networks and social contexts, networks and game theory, information diffusion and community detection. We shall discuss both classic questions about networks (how to model the spread of disease, what kinds of networks support decentralized search?) as well as more recent questions on networks with attributes and how to analyze massive networks efficiently. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
31531	Online	ISE	ARRANGED	n.a.	n.a.	Caesar, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Special Approval: Instructor Approval Required Credit: 4 hours Section Title: IOT Software Engineering Section Info: Description: Students will gain exposure to software engineering principals through design and implementation of a large-scale cloud IoT software system. Students will gain real-world experience, working in teams to construct and refine a large software base. Each team will focus on a part of the software (graphical frontend, cloud backend, algorithm core, etc.) and will be expected to have or acquire the skills needed to contribute. We will work together to build something real; at the end of the semester, students will gain operational experience through deployment of their useful system on the Internet and make it available for users across the world. The focus of this class will be on cloud IoT and the development of software platforms that drive IoT applications, as opposed to hardware or wireless concepts covered in other courses. Prerequisites: solid programming experience (e.g., CS 241, 242, 438, 423), and consent of instructor (please email your CV to caesar@illinois.edu to request enrollment). Restriction(s): Not intended for First Time Freshman students.
72154	Online	IT3	12:30PM -1:45PM	R	n.a.	Caesar, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Internet of Things Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. 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. This course will be taught on the Coursera platform, and will include in-class meetings as scheduled for additional discussion time. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister
72155	Online	IT4	12:30PM -1:45PM	R	n.a.	Caesar, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Internet of Things Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. 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. This course will be taught on the Coursera platform, and will include in-class meetings as scheduled for additional discussion time. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
42449	Online	ITO	ARRANGED	n.a.	n.a.	Caesar, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 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 or MCS:Computer Sci Online -UIUC.
70198	Online	KA3	11:00AM -12:30PM	TR	n.a.	Kirlik, A	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Experimental Methods for HCI Section Info: This course covers conceiving, designing, performing, analyzing data and reporting the results of experiments and usability/UX tests in HCI and empirically evaluating interactive technologies in engineering generally. Topics include defining research questions, selecting experimental objects, tasks, and participants, the ethical protection of subjects, selecting experimental designs, mitigating threats to validity, the collection and analysis of both qualitative and quantitative data, and reporting experimental research in publications. Both parametric and nonparametric data analysis are covered, including the most commonly used inferential statistical tests such as repeated- and independent-measures ANOVA, post-hoc Tukey, Wilcoxon, Mann-Whitney, Kruskal-Wallis and others. Statistical material is taught using methods based on mathematical foundations rather than with statistical software languages or packages in order to provide both a rigorous and intuitive understanding to complement the convenience these programming environments provide in research practice. Grades are based mainly on homework and 2 exams.
70462	Online	KA4	11:00AM -12:30PM	TR	n.a.	Kirlik, A	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Experimental Methods for HCI Section Info: This course covers conceiving, designing, performing, analyzing data and reporting the results of experiments and usability/UX tests in HCI and empirically evaluating interactive technologies in engineering generally. Topics include defining research questions, selecting experimental objects, tasks, and participants, the ethical protection of subjects, selecting experimental designs, mitigating threats to validity, the collection and analysis of both qualitative and quantitative data, and reporting experimental research in publications. Both parametric and nonparametric data analysis are covered, including the most commonly used inferential statistical tests such as repeated- and independent-measures ANOVA, post-hoc Tukey, Wilcoxon, Mann-Whitney, Kruskal-Wallis and others. Statistical material is taught using methods based on mathematical foundations rather than with statistical software languages or packages in order to provide both a rigorous and intuitive understanding to complement the convenience these programming environments provide in research practice. Grades are based mainly on homework and 2 exams. Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, NDEG:Computer Science Onl-UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
43500	Online	MC1	2:00PM -3:15PM	WF	n.a.	Davis, N	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Martian Computing Section Info: This course will be online synchronously. The underlying infrastructure of modern networked computing—namely Unix and its derivatives—is approaching fifty years of age. What will come to replace it? A strong competitor is the clean-slate “operating function” approach of Urbit. Jocosely branded as “computing for Martians,” Urbit provides a fresh and updated vision of what Internet computing could come to look like in future years. Featuring end-to-end encryption and true peer-to-peer routing built on a network-first operating system, Urbit fosters decentralized digital societies and stable user identities. Our primary objectives in this course are for you to be able to explain and navigate the technical layout of Urbit, as well as construct novel applications for Arvo, the Urbit operating function, using the Hoon programming language. Lessons focus on conceptual or architectural aspects of Urbit, including technical discussions of Urbit’s behavior and internals. Labs are hands-on tutorials to familiarize students with operations and language features. Graduate students in computer science and neighboring fields interested in sound computing and functional operating system design (functional-as-in-language). The course assumes an interest in functional programming but no specific experience. Suggested for students in computer science and neighboring fields interested in sound computing and functional operating system design (functional-as-in-language). The course assumes an interest in functional programming but no specific experience. Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
49190	Online	MP3	11:00AM -12:15PM	TR	n.a.	Parthasarathy, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: Logic in Computer Science Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. This course will provide an introduction to mathematical logic from the perspective of computer science, emphasizing proof systems, decidable fragments, connections to computability and complexity, and decision algorithms. The topics covered will be motivated by applications in artificial intelligence, machine learning logics, databases, formal verification and theoretical computer science. The goal of the course is to prepare students for using logic as an effective tool in computer science, with associated tools.
49191	Online	MP4	11:00AM -12:15PM	TR	n.a.	Parthasarathy, M	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Logic in Computer Science Section Info: There will be asynchronous recorded lectures and additional synchronous online activities. This course will provide an introduction to mathematical logic from the perspective of computer science, emphasizing proof systems, decidable fragments, connections to computability and complexity, and decision algorithms. The topics covered will be motivated by applications in artificial intelligence, machine learning logics, databases, formal verification and theoretical computer science. The goal of the course is to prepare students for using logic as an effective tool in computer science, with associated tools. Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC.
66825	Lecture	RK1	ARRANGED	n.a.	Location Pending		Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 3 hours Section Title: The Art of Web Programming
66826	Lecture	RK2	2:00PM -3:15PM	MW	Location Pending	Kumar, R	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: The Art of Web Programming Restriction(s): Restricted to Computer Science major(s). Restricted to Graduate - Urbana-Champaign.