MATH 490

Fall 2023 All Classes

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Advanced Topics in Mathematics

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Credit: 1 TO 4 hours.

Deals with selected topics and applications of mathematics; see Class Schedule or department office for current topics.

1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated with approval. Prerequisite: Consent of instructor.

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MATH 490 class schedule data for fall 2023
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
48560	Online	KK	11:00AM -12:20PM	TR	n.a.	Kirkpatrick, K	Part of Term: 1 Date Range: 08/21/23-12/06/23 Credit: 3 hours Section Title: Math of Machine Learning Section Info: Mathematics of Machine Learning. Prerequisite: Math 461 or Stat 410 and one of CS 101 or 124 or equivalent. Description: Machine learning is a growing field at the intersection of probability, statistics, optimization, and computer science, which aims to develop algorithms for making predictions based on data. This course will cover foundational models and mathematics for machine learning, including statistical learning theory and neural networks, with a project component.
61255	Lecture-Discussion	QIT	10:00AM -10:50AM	MWF	307 David Kinley Hall	Araiza, R	Part of Term: 1 Date Range: 08/21/23-12/06/23 Credit: 3 hours Section Title: Quantum Information Theory Section Info: Prerequisite: Math 416 or equivalent proof-based linear algebra. No prior knowledge of quantum physics is expected. Introduction to the mathematical aspects of quantum information theory. Main topics include quantum channels and decoherence, and quantum error correction. For more information please see https://go.math.illinois.edu/registration
54837	Online	XGR	ARRANGED	n.a.	n.a.	DeVille, L	Part of Term: 1 Date Range: 08/21/23-12/06/23 Credit: 3 hours Section Title: Math of Machine Learning Section Info: This course is available to undergrads and non-degree students as an online Academic Year term offering. See https://netmath.illinois.edu/college/math-490 XGR Section restricted to Engineering Online graduate degree-seeking students in MSAE, MSCE, MCS, MSIE, and MSME degree students. For more details on this course section, please see http://engineering.illinois.edu/online/courses/ Mathematics of Machine Learning. Prerequisite: Math 461 or Stat 410 and one of CS 101 or 124 or equivalent. Description: Machine learning is a growing field at the intersection of probability, statistics, optimization, and computer science, which aims to develop algorithms for making predictions based on data. This course will cover foundational models and mathematics for machine learning, including statistical learning theory and neural networks, with a project component. Restriction(s): Restricted to MS: Civil Engr - Online - UIUC, MCS:Computer Sci Online -UIUC, MS:Industrial Engr Online-UIUC, MS:Mechanical Engineerng -UIUC, MS:Env Engr CivilEngr ONL-UIUC, MS: Aerospace Engr-Online-UIUC, MENG:Engr:Energy Sys Onl-UIUC, MENG:Mech Engineering Onl-UIUC, MENG:Engr:AeroSys Online- UIUC, or MENG:Engr:Plasma Online-UIUC.