CS 498

Spring 2019 All Classes

All Classes

Special Topics

SHOW FINAL EXAM SCHEDULE

Credit: 1 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.

My Favorites

My Schedule

Section Status updates every 10 minutes.

CS 498 class schedule data for spring 2019
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
61698	Laboratory	AB1	9:00AM -10:50AM	F	0222 Siebel Center for Comp Sci	Bambenek, J	Part of Term: 1 Date Range: 01/14/19-05/01/19 Section Title: Digital Forensics II Section Info: This lab section will meet in 0222 Siebel Center
65904	Laboratory	AB2	11:00AM -12:50PM	F	0222 Siebel Center for Comp Sci	Bambenek, J	Part of Term: 1 Date Range: 01/14/19-05/01/19 Section Title: Digital Forensics II
69364	Lecture-Discussion	ABD	12:30PM -1:45PM	TR	1310 Digital Computer Laboratory	Chekuri, C	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Algorithms for Big Data Section Info: Algorithms for Big Data 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, and sparsification methods, with applications to signals, matrices, and graphs. Emphasis will be on theoretical aspects of the design and analysis of such algorithms. Prerequisite: grades of at least B+ in CS 374 and CS 361, or comparable understanding and facility with algorithms and probability.
61697	Lecture	AL1	9:00AM -9:50AM	MW	1302 Siebel Center for Comp Sci	Bambenek, J	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Digital Forensics II Section Info: This is a course for graduate students and advanced undergraduates wanting to develop greater depth and breadth in digital forensics and assumes a basic knowledge of the material covered in Digital Forensics I. Topics include standards of evidence, investigatory procedures, forms of investigation, legal procedures, reasoning about evidence, psychology of cyber crime, anti-forensics, multimedia forensics, computer forensics, web browser forensics, embedded systems forensics, network forensics, cloud forensics, applications forensics, and fraud examination. It introduces known barriers and open challenges in the field. Prerequisite: Completion of Digital Forensics I or special permission granted by the instructor.
65685	Lecture	AML	3:30PM -4:45PM	TR	1320 Digital Computer Laboratory	Walker, T	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Applied Machine Learning Section Info: Techniques of machine learning, with applications to various signal problems. Techniques covered will be: regression including linear regression, multiple regression, regression forests and nearest neighbors regression; classification with various methods including logistic regression, support vector machines, nearest neighbors, simple boosting and decision forests; clustering with various methods including basic agglomerative clustering and k-means; resampling methods, including cross-validation and the bootstrap; model selection methods, including AIC, stepwise selection and the lasso; hidden Markov models; model estimation in the presence of missing variables; and neural networks, including deep networks. 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. Prereq: A course in probability or statistics, a course in linear algebra, and some programming experience
67942	Online	AMO	ARRANGED	n.a.	n.a.	Walker, T	Part of Term: 1 Date Range: 01/14/19-05/01/19 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 Coursera ID verification and ProctorU fees may apply. Description:Techniques of machine learning, with applications to various signal problems. Techniques covered will be: regression including linear regression, multiple regression, regression forests and nearest neighbors regression; classification with various methods including logistic regression, support vector machines, nearest neighbors, simple boosting and decision forests; clustering with various methods including basic agglomerative clustering and k-means; resampling methods, including cross-validation and the bootstrap; model selection methods, including AIC, stepwise selection and the lasso; hidden Markov models; model estimation in the presence of missing variables; and neural networks, including deep networks. 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.
69511	Online	CCA	ARRANGED	n.a.	n.a.	Farivar, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Cloud Computing Applications Section Info: Restricted to CS online MCS Students. ProctorU and other fees may apply. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC.
68121	Lecture-Discussion	DSG	12:30PM -1:50PM	MW	1310 Digital Computer Laboratory	Campbell, R Iyer, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Data Science & Analytics Restriction(s): Restricted to Graduate - Urbana-Champaign.
65868	Online	DSO	ARRANGED	n.a.	n.a.	Farivar, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Cloud Computing Applications Section Info: This course is only for students that are in the Computer Science MCS-DS Program. Additional Coursera ID verification and ProctorU fees may apply. Restriction(s): Restricted to NDEG:Computer Science Onl-UIUC or MCS:Computer Sci Online -UIUC.
68120	Lecture-Discussion	DSU	12:30PM -1:50PM	MW	1310 Digital Computer Laboratory	Campbell, R Iyer, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Data Science & Analytics
69336	Online	GA	ARRANGED	n.a.	n.a.	Agha, G	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Smart Cities Section Info: CS 498 Smart Cities: Concepts and Technologies The cities of the future will incorporate innovative information technology to optimize water management, power grid, transportation network, communication network, administrative services, and social spaces. The course will provide a technical introduction to relevant computer science concepts and how they are applied to smart cities. Topics covered will include sensor/actuator networks, crowd sourcing, data science, computer security, privacy, and artificial intelligence. Perspectives on potential implications of these technologies for urban living will be also be discussed. Restriction(s): Restricted to O/C Engineering City Scholars students.
69419	Lecture-Discussion	IT3	9:30AM -10:45AM	MW	1109 Siebel Center for Comp Sci	Caesar, M	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 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.
69420	Lecture-Discussion	IT4	9:30AM -10:45AM	MW	1109 Siebel Center for Comp Sci	Caesar, M	Part of Term: 1 Date Range: 01/14/19-05/01/19 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 Graduate - Urbana-Champaign.
69828	Online	ITF	ARRANGED	n.a.	n.a.	Caesar, M	Part of Term: 1 Date Range: 01/14/19-05/01/19 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.
69725	Online	ITO	ARRANGED	n.a.	n.a.	Caesar, M	Part of Term: 1 Date Range: 01/14/19-05/01/19 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 Graduate - Urbana-Champaign. Restricted to MCS:Computer Sci Online -UIUC.
69348	Online	MD	ARRANGED	R	n.a.	Bailey, B	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Mobile Interactive Design Restriction(s): Restricted to O/C Engineering City Scholars students.
69337	Lecture	MID	3:00PM -5:20PM	W	1109 Siebel Center for Comp Sci	Bailey, B	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Mobile Interactive Design Section Info: In this course, students will learn how to imagine, implement, and evaluate novel mobile experiences. Topics will include user research, prototyping, field studies, user interface architectures, touch and in-air gestures, and sensors; as applied to a mobile context. Students will also learn design thinking skills, design communication skills, and team work skills. The class format is lecture, individual and group activities, and discussion. Class attendance and participation is expected. Students cannot receive credit for both CS 465 and CS 498 BPB.
65864	Online	ONL	ARRANGED	n.a.	n.a.	Walker, T	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Applied Machine Learning Section Info: Restricted to CS online MCS Students. ProctorU and other fees may apply. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC.
39660	Lecture	PS3	12:30PM -1:45PM	TR	2310 Everitt Laboratory	Smaragdis, P	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Audio Computing Lab Section Info: This course will cover the computational foundations of modern audio applications. This will be a lab-like course in which students will be required to bring in their laptops in class and collectively implement a variety of core audio operations that are commonplace today. In this class we will cover the necessary theory to start working on audio processing, and implement a variety of applications such as room and 3D/virtual audio rendering, pitch manipulations and autotuning, denoising for communications and forensics, audio classification, music information retrieval based on audio, rudimentary speech recognition, speech and audio coding, applications of machine learning to audio scene recognition, audio restoration, missing data recovery, and many more. Students will need to have a good grasp of programming in Python (or MATLAB) and will be required to bring to class their laptops and headphones to participate in lab exercises. Suggested prerequisites include MATH416 (or equivalent) and CS241.
67074	Lecture	PS4	12:30PM -1:45PM	TR	2310 Everitt Laboratory	Smaragdis, P	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Audio Computing Lab Section Info: This course will cover the computational foundations of modern audio applications. This will be a lab-like course in which students will be required to bring in their laptops in class and collectively implement a variety of core audio operations that are commonplace today. In this class we will cover the necessary theory to start working on audio processing, and implement a variety of applications such as room and 3D/virtual audio rendering, pitch manipulations and autotuning, denoising for communications and forensics, audio classification, music information retrieval based on audio, rudimentary speech recognition, speech and audio coding, applications of machine learning to audio scene recognition, audio restoration, missing data recovery, and many more. Students will need to have a good grasp of programming in Python (or MATLAB) and will be required to bring to class their laptops and headphones to participate in lab exercises. Suggested prerequisites include MATH416 (or equivalent) and CS241. Restriction(s): Restricted to Graduate - Urbana-Champaign.
61851	Lecture	RK1	11:00AM -12:15PM	MW	0216 Siebel Center for Comp Sci	Kumar, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Art and Science of Web Prog Section Info: Presents client- and server-side technologies that enable modern Web applications. Topics include the building blocks of the Web (HTML, CSS, the Document Object Model, Javascript) and data exchange (HTTP, JSON, RESTful APIs, and SQL/NoSQL databases). Programming assignments will expose students to CSS preprocessors, grid systems, and full-stack Javascript frameworks that scaffold development and testing. In addition, students will work in teams to design, implement and deploy a full-featured web application. Prerequisites: CS225.
61850	Lecture	RK2	11:00AM -12:15PM	MW	0216 Siebel Center for Comp Sci	Kumar, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Art and Science of Web Prog Section Info: Presents client- and server-side technologies that enable modern Web applications. Topics include the building blocks of the Web (HTML, CSS, the Document Object Model, Javascript) and data exchange (HTTP, JSON, RESTful APIs, and SQL/NoSQL databases). Programming assignments will expose students to CSS preprocessors, grid systems, and full-stack Javascript frameworks that scaffold development and testing. In addition, students will work in teams to design, implement and deploy a full-featured web application. Prerequisites: CS225. Restriction(s): Restricted to Graduate - Urbana-Champaign.
69525	Online	RK3	ARRANGED	n.a.	n.a.	Kumar, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Art and Science of Web Prog Section Info: Presents client- and server-side technologies that enable modern Web applications. Topics include the building blocks of the Web (HTML, CSS, the Document Object Model, Javascript) and data exchange (HTTP, JSON, RESTful APIs, and SQL/NoSQL databases). Programming assignments will expose students to CSS preprocessors, grid systems, and full-stack Javascript frameworks that scaffold development and testing. In addition, students will work in teams to design, implement and deploy a full-featured web application. Prerequisites: CS225. Those registered for this section will watch recordings from lecture of RK2.
69526	Online	RK4	ARRANGED	n.a.	n.a.	Kumar, R	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Art and Science of Web Prog Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC.
69469	Lecture-Discussion	SM	2:00PM -3:20PM	MW	3015 Electrical & Computer Eng Bldg	Mitra, S Mohan, S	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Principles of Safe Autonomy
50232	Lecture	VR3	4:00PM -5:15PM	MW	1320 Digital Computer Laboratory	Shaffer, E	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 3 hours Section Title: Virtual Reality
50234	Lecture	VR4	4:00PM -5:15PM	MW	1320 Digital Computer Laboratory	Shaffer, E	Part of Term: 1 Date Range: 01/14/19-05/01/19 Credit: 4 hours Section Title: Virtual Reality Restriction(s): Restricted to Graduate - Urbana-Champaign.