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4
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70464
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Lecture
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AI1
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2:00PM
-3:20PM
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TR
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Location Pending
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Ray Chaudhury, B
Xu, Y
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- Availability:
- CrossListOpen (Restricted)
- Part of Term:
- 1
- Date Range:
- 08/24/26-12/09/26
- Credit:
- 3 hours
- Section Title:
- AI, Markets, and Game Theory
- Section Info:
- Prerequisite: IE 300 or equivalent probability and statistics course; IE 310 or equivalent optimization course; MATH 257 or equivalent linear algebra course. Description: Explores the intersection of artificial intelligence and game theory with applications to markets and multi-agent systems. Covers fundamentals of AI and game theory, then examines three critical intersections: (1) AI for Game Solving—scalable methods for equilibrium computation and solving large-scale imperfect-information games; (2) AI in Markets—how learning algorithms create economic value, with applications to recommendation systems; and (3) Game Theory for Multi-Agent AI—how strategic incentives and mechanism design can improve the safety, robustness, and efficiency of autonomous systems, including the detection and prevention of algorithmic collusion.
- Restriction(s):
-
Restricted to Civil Engineering or Computer Engineering or Computer Science or Electrical Engineering or Engineering Mechanics or Engineering Physics or Industrial Engineering or Materials Science & Engr or Mechanical Engineering or Chemical Engineering or Applied Mathematics or Statistics or Bioengineering or Mathematics or Actuarial Mathematics or Aerospace Engineering or Agricultural & Biological Engr or Nuclear, Plasma, Radiolgc Engr or Systems Engineering and Design major(s). Restricted to students with Junior or Senior class standing.
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4
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70465
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Lecture
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AI2
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2:00PM
-3:20PM
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TR
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Location Pending
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Ray Chaudhury, B
Xu, Y
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- Availability:
- CrossListOpen (Restricted)
- Part of Term:
- 1
- Date Range:
- 08/24/26-12/09/26
- Credit:
- 4 hours
- Section Title:
- AI, Markets, and Game Theory
- Section Info:
- Prerequisite: IE 300 or equivalent probability and statistics course; IE 310 or equivalent optimization course; MATH 257 or equivalent linear algebra course. Description: Explores the intersection of artificial intelligence and game theory with applications to markets and multi-agent systems. Covers fundamentals of AI and game theory, then examines three critical intersections: (1) AI for Game Solving—scalable methods for equilibrium computation and solving large-scale imperfect-information games; (2) AI in Markets—how learning algorithms create economic value, with applications to recommendation systems; and (3) Game Theory for Multi-Agent AI—how strategic incentives and mechanism design can improve the safety, robustness, and efficiency of autonomous systems, including the detection and prevention of algorithmic collusion.
- Restriction(s):
-
Restricted to Graduate - Urbana-Champaign. Not intended for NDEG:Graduate OR - UIUC.
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3
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76213
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Lecture-Discussion
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ML
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9:30AM
-10:50AM
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TR
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162 Education Building
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Murphy, M
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- 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):
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Not intended for students with Freshman class standing.
Not intended for First Time Freshman students.
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1
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48514
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Lecture-Discussion
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MM
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2:00PM
-3:20PM
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TR
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218 Ceramics Building
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Murphy, M
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- Availability:
- Open
- Part of Term:
- B
- Date Range:
- 10/19/26-12/09/26
- Credit:
- 2 hours
- Section Title:
- Blockchain and Cryptocurrency
- Section Info:
- Blockchain and Cryptocurrency Seminar explores the principles, technologies, and applications underlying decentralized systems and digital assets. This course is designed specifically for graduate students seeking a rigorous introduction to blockchain architecture, consensus mechanisms, smart contracts, and cryptocurrency markets. It emphasizes hands-on coding exercises and practical implementation using Python and relevant blockchain frameworks. Students will learn the concepts behind distributed ledgers, cryptographic security, and token economics, and will develop projects that simulate real-world blockchain use cases. The seminar also prepares students for advanced topics in decentralized finance (DeFi), digital asset valuation, and emerging trends in Web3. Priority given to MS Financial Engineering Program students, ISE students, and other by permission of instructor. Engineering undergraduates with junior or senior status will be considered if space is available.
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3
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50209
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Lecture-Discussion
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SC
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9:00AM
-11:50AM
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S
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4039 Campus Instructional Facility
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Prasad, I
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- 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):
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Restricted to Graduate - Urbana-Champaign. Restricted to MS: Financial Engineering.
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