IE 498

Fall 2026 Part of Term A

Part of Term A
Aug 24-Oct 16

Special Topics

Credit: 1 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.

1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary to a maximum of 9 hours.

My Favorites

My Schedule

Section Status updates every 10 minutes.

IE 498 class schedule data for fall 2026
	Status		CRN	Type	Section	Time	Day	Location	Instructor	Section Details
			76213	Lecture-Discussion	ML	9:30AM -10:50AM	TR	Location Pending	Murphy, M	Availability: Open (Restricted) Part of Term: A Date Range: 08/24/26-10/16/26 Credit: 2 hours Section Title: Machine Learning in Fin Lab Section Info: Machine Learning includes the design and the study of algorithms that can learn from experience, improve their performance, and make predictions. Students will learn the concepts behind different supervised machine learning algorithms (KNN, decision trees, logistic and linear regression, SVM, random forest, and gradient boosting) and implement them in Python using packages; pandas, NumPy and scikit-learn. All the data for this course features unique real-world financial datasets. Electronic Trading, informally known as “High Frequency Trading”, will teach students both the core concepts and underlying mechanics of, step by step, message by message, bit for bit, exactly how trillions of dollars in notional value are automatically traded daily around the globe. Electronic Trading will provide students with an exciting introduction both to the modern world of automated finance and to many exciting technologies that power it. Where does the “actual” real-time price of a particular asset come from at any point in time? How exactly is it being calculated and by who or what? Is there even a single price or are there multiple, and are any of those prices actually correct? How quickly can the price change or suddenly stop changing after plummeting? How do markets break or pricing models fail? Priority given to incoming MS Financial Engineering Program students. Restriction(s): Not intended for students with Freshman class standing. Not intended for First Time Freshman students.
			50209	Lecture-Discussion	SC	9:00AM -11:50AM	S	Location Pending	Prasad, I	Availability: Open (Restricted) Part of Term: A Date Range: 08/24/26-10/16/26 Credit: 2 hours Section Title: Structured Credit I Section Info: Asset-backed financing is important to understand because it illustrates a fundamental aspect of how financial markets and lending work in the economy. By securitizing assets like mortgages, auto loans, or student loans, financial institutions can create investment opportunities that provide liquidity and lower borrowing costs for borrowers. This process not only facilitates access to funds for individuals and businesses but also spreads risk across a wider pool of investors. Grasping the concept of asset-backed financing helps students understand the mechanisms behind loans and fixed income investments, highlighting how diverse financial instruments can be used to allocate capital efficiently and support economic growth. We will especially focus on the mortgage-backed securities market, loan performance analytics and investment thesis considered by professionals. The course introduces aspects of the mortgage and MBS markets, prepayment and default modeling, structuring of RMBS bonds, and more. Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to MS: Financial Engineering.