Classes Offered - USC Schedule of Classes

Industrial and Systems Engineering (ISE)

https://ise.usc.edu
D class assignments for undergraduates available in GER-247; Phone: (213) 740-4893.
(213) 740-4893. 7 D class assignments for undergraduates and on-campus graduate students available online at ise.usc.edu/current-students/ or via phone at (213) 740-4893. 7 D class assignments for undergraduates available in GER247; phone

Crosslist ISE 487: Enterprise Data Analytics (4.0 units)

Methodology to store, organize, cleanse, harmonize and stage enterprise data for analytics. Report, visualize, slice and dice, forecast and predict trends.

Prerequisite: 1 from (ITP 249 or ITP 320 or DSCI 351)
Crosslist: This course is offered by the ITP department but may qualify for major credit in ISE. To register, enroll in ITP 487.

Section	Session	Type	Time	Days	Registered	Instructor	Location	Syllabus	Info
31845R	050	Lecture	10:30-1:20pm	MWF	15 of 40	Nitin Kale	ONLINE	PDF (379959 KB)

Crosslist ISE 560: Analysis of Algorithms (4.0 units)

Explores fundamental techniques such as recursion, Fourier transform ordering, dynamic programming for efficient algorithm construction. Examples include arithmetic, algebraic, graph, pattern matching, sorting, searching algorithms.

Crosslist: This course is offered by the CSCI department but may qualify for major credit in ISE. To register, enroll in CSCI 570.

Section	Session	Type	Time	Days	Registered	Instructor	Location
29963D	901	Lecture	1:10-3:15pm	MTuWTh	32 of 120	Victor Adamchik	OHE122
29964R	901	Discussion	TBA	TBA	32 of 120		OFFICE
29965R	901	Quiz	TBA	TBA	32 of 120		OFFICE
29928D	902	Lecture	4:00-6:50pm	MWTh	83 of 120	Shahriar Shamsian	OHE122
29929R	902	Discussion	TBA	TBA	83 of 120		OFFICE
29930R	902	Quiz	TBA	TBA	83 of 120		OFFICE
29966D	909	Lecture	1:10-3:15pm	MTuWTh	3 of 30	Victor Adamchik	DEN@Viterbi
29967R	909	Discussion	TBA	TBA	3 of 30		DEN@Viterbi
29968R	909	Quiz	TBA	TBA	3 of 30		DEN@Viterbi
29931D	910	Lecture	4:00-6:50pm	MWTh	25 of 40	Shahriar Shamsian	DEN@Viterbi
29932R	910	Discussion	TBA	TBA	25 of 40		DEN@Viterbi
29933R	910	Quiz	TBA	TBA	25 of 40		DEN@Viterbi

Crosslist ISE 568: Machine Learning (4.0 units)

Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.

Crosslist: This course is offered by the CSCI department but may qualify for major credit in ISE. To register, enroll in CSCI 567.

Section	Session	Type	Time	Days	Registered	Instructor	Location
29922D	901	Lecture	10:30-12:35pm	MTuWTh	29 of 120	Victor Adamchik	OHE122
29923R	901	Discussion	TBA	TBA	29 of 120		OFFICE
29924R	901	Quiz	TBA	TBA	29 of 120		OFFICE
29925D	909	Lecture	10:30-12:35pm	MTuWTh	9 of 30	Victor Adamchik	DEN@Viterbi
29926R	909	Discussion	TBA	TBA	9 of 30		DEN@Viterbi
29927R	909	Quiz	TBA	TBA	9 of 30		DEN@Viterbi

ISE 590: Directed Research (1.0-12.0 units)

Research leading to the master's degree; maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Section	Session	Units	Type	Time	Days	Registered	Instructor	Location
31590D	908	1.0-5.0	Lecture	TBA	TBA	1 of 5	John Carlsson	OFFICE
31594D	908	1.0-4.0	Lecture	TBA	TBA	2 of 5	Stephen Lu	OFFICE
31595D	908	1.0-5.0	Lecture	TBA	TBA	1 of 5	David Belson	OFFICE
31596D	908	1.0-5.0	Lecture	TBA	TBA	1 of 5	Giacomo Nannicini	OFFICE

ISE 594z: Master's Thesis (0.0 units)

Credit on acceptance of Thesis.

Prerequisite: ISE 594B
Restriction: Registration open to the following class level(s): Master Student

Section	Session	Type	Time	Days	Registered	Instructor	Location	Syllabus	Info
31593D	908	Lecture	TBA	TBA	1 of 5	Randolph Hall	OFFICE

ISE 599: Special Topics (2.0-4.0 units, max 9)

Course content will be selected each semester to reflect current trends and developments in the field of industrial and systems engineering.

Section	Session	Units	Type	Time	Days	Registered	Instructor	Location	Syllabus	Info
Introduction to Deep Learning
31591D	902	3.0	Lecture	9:00-10:40am	Mon, Wed	8 of 35	Cesar Acosta-Mejia	KAP145	PDF (306922 KB)

ISE 790: Research (1.0-12.0 units)

Research leading to the doctorate. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Section	Session	Units	Type	Time	Days	Registered	Instructor	Location
31707D	901	2.0	Lecture	TBA	TBA	1 of 5	Maged Dessouky	OFFICE
31708D	901	2.0-6.0	Lecture	TBA	TBA	0 of 5		OFFICE
31709D	902	1.0-12.0	Lecture	TBA	TBA	1 of 5	Ali Abbas	OFFICE
31710D	901	1.0-5.0	Lecture	TBA	TBA	1 of 5	Petros Ioannou	OFFICE
31711D	901	1.0-5.0	Lecture	TBA	TBA	2 of 5	Phebe Vayanos	OFFICE
31712D	901	1.0-5.0	Lecture	TBA	TBA	1 of 5	Detlof Von Winterfeldt	OFFICE