IE 598

Fall 2020 All Classes

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Credit: 0 TO 4 hours.

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

Approved for letter and S/U grading. May be repeated in the same or separate terms if topics vary.

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IE 598 class schedule data for fall 2020
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
72015	Online	AW	9:00AM -10:20AM	MW	n.a.	Wooldridge, A	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Job and Organization Design Section Info: Prerequisites: IE 340 credit is recommended. The purpose of this course is to understand models and theories of job and organization job, to be able to answer the questions “What makes for a good job?” and “What makes for a bad job?” Students will be able to apply models and theories of job and organization design to the analysis and redesign of jobs – to figure out how to improve a “bad” job, and ideally make it a good one. Finally, we will talk about processes to use to implement job redesigns. The IE 598 offering will include all of the material and assignments as IE 498, in addition to each student developing their own research proposal based on course material. Restriction(s): Restricted to Graduate - Urbana-Champaign.
75767	Online	CSQ	5:30PM -8:30PM	W	n.a.	Lariviere, D	Date Range: 10/28/20-11/24/20 Section Title: Computer Science for Quants Section Info: Virtually all aspects of modern finance are now heavily reliant on both technology and computer science. Software engineering has become an increasingly useful and often even essential skill and discipline for those intending to work in the financial industry. This two week course is intended to offer advanced students an ultra accelerated deep-dive into many of the essential aspects, both academic and professional, of computer science and software development to the students of the MSFE and MSF programs. The underlying motivation of this course is to provide students from non-CS backgrounds with the additional exposure, knowledge, and skills often required in order to secure employment in the financial industry in roles requiring or substantially benefiting from software development or data analytics. Topics covered will include the most important aspects of a variety of topics, including: core foundational aspects of computer science (data structures and algorithms, discrete math, boolean logic and algebra, scientific computation, computer architecture, computer networking, operating systems, programming languages and compilers, and databases), professional software developer tools and best practices (object-oriented programming, various IDEs and software debugging methods, unit and integration testing, version control systems, continuous integration, bug tracking, project management, devops, and software design patterns) and various continuing high demand topics and skills in industry (Big Data, AI/ML, cloud computing and virtualization, enterprise system architecture, computer security, and high availability and fault-tolerant design). Restriction(s): Restricted to MS: Finance Cost Rec - UIUC, MS: Financial Engineering, MS:Finance -UIUC, or MS: Finance - UIUC.
54643	Online	FHC	2:00PM -4:50PM	M	n.a.	Wooldridge, A	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Field Research in Health Care Section Info: -Students will learn about the methodological and practical issues of field research methods with special emphasis on mixed methods research. -Students will develop their own research proposal (e.g., Master’s thesis, Ph.D. dissertation, research proposal). This graduate seminar is designed for graduate students interested or involved in field research, in particular in the areas of human factors and ergonomics, health systems engineering, quality management and engineering, and other domains related to healthcare quality and patient safety. Restriction(s): Restricted to Graduate - Urbana-Champaign.
65637	Online	YZ	3:30PM -4:50PM	TR	n.a.	Zhou, Y	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Online Lrning & Decisn Making Section Info: Prerequisites: background in basic probability theory. linear algebra, and algorithm design and analysis. This course covers several foundational topics in online learning and sequential decision making under uncertainty, a subject on the intersection of algorithms, machine learning, and operations research. Such problems have wide applications in online advertising, recommendation systems, crowdsourcing, revenue management, etc. In this course, we will study the problems that usually feature the tension between how to collect data and utilize the data to make optimal sequential decisions (a.k.a. the exploration and exploitation dilemma). We cover both fundamental results and research frontiers. We focus on algorithmic results, and introduce lower bounds as well. Restriction(s): Restricted to Graduate - Urbana-Champaign.