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Data Science (DSCI)
- datascience.usc.edu/ D class assignments are only avaialable online at: myviterbi.usc.edu. Once you create your myViterbi profile, select the "D-Clearance Request Manager" to submit requests for DSCI courses. To be enrolled in an off-campus course, you MUST also be enrolled in the Distance Education Network (DEN). For more information, call 740-4488 or go to den.usc.edu. DEN courses are indicated by a location of DEN@Viterbi. For general questions regarding DSCI courses, you may email datasci@usc.edu.
Data modeling, data storage, indexing, relational databases, key-value/document store, NoSQL, distributed file system, parallel computation and big-data analytics.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32400R | 001 | Lecture | 10:00-11:50am | Mon, Wed | 34 of 36 | Wensheng Wu | THH106 | PDF (204465 KB) |
Programming in Python for retrieving, searching and analyzing data from the Web. Learning to manipulate large data sets.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32429D | 048 | Lecture | 9:00-10:50am | Wednesday | 45 of 46 | Anna Farzindar | GFS116 | PDF (235417 KB) | |
32430R | 048 | Lab | 12:00-1:50pm | Wednesday | 45 of 46 | ZHS352 | |||
32431D | 048 | Lecture | 10:00-10:50am | Mon, Wed | 44 of 44 | Ulf Hermjakob | WPH102 | PDF (167048 KB) | |
32433R | 048 | Lab | 9:00-9:50am | Mon, Wed | 44 of 44 | WPHB28 | |||
32434D | 048 | Lecture | 4:00-5:50pm | Wednesday | 44 of 45 | Jose-Luis Ambite | RTH109 | PDF (147646 KB) | |
32435R | 048 | Lab | 4:00-5:50pm | Thursday | 44 of 45 | RTH109 | |||
32440D | 034 | Lecture | 4:00-5:50pm | Wednesday | 21 of 24 | Jose-Luis Ambite | DEN@Viterbi | PDF (147646 KB) | |
32441R | 034 | Lab | 4:00-5:50pm | Thursday | 21 of 24 | DEN@Viterbi |
Analysis of computer security and why systems are not secure. Concepts and techniques applicable to the design of hardware and software for Trusted Systems.
- Prerequisite: DSCI 519
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32408D | 048 | Lecture | 2:00-5:20pm | Monday | 7 of 25 | Tanya Ryutov | OHE100C | PDF (303542 KB) | |
32424D | 034 | Lecture | 2:00-5:20pm | Monday | 13 of 20 | Tanya Ryutov | DEN@Viterbi | PDF (303542 KB) |
Covers societal implications of information privacy and how to design systems to best preserve privacy. Recommended preparation: general familiarity with the use of common Internet and mobile applications.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32410D | 048 | Lecture | 12:00-3:20pm | Friday | 73 of 76 | Clifford Neuman | OHE136 | ||
32425D | 034 | Lecture | 12:00-3:20pm | Friday | 29 of 40 | Clifford Neuman | DEN@Viterbi |
Basic and advanced fairness concepts and methods; applications to societal data for studying fairness and bias; fairness and bias effects in learning algorithms.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
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32427D | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 52 of 53 | Kristina Lerman,Fred Morstatter | SOSB4 | PDF (225289 KB) |
Introduction to data analysis techniques and associated computing concepts for non-programmers. Topics include foundations for data analysis, visualization, parallel processing, metadata, provenance and data stewardship. Recommended preparation: mathematics and logic undergraduate courses.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32411D | 048 | Lecture | 2:00-5:20pm | Monday | 42 of 40 | Ning Wang | RTH109 | ||
32442D | 034 | Lecture | 2:00-5:20pm | Monday | 10 of 20 | Ning Wang | DEN@Viterbi |
Fundamentals of big data informatics techniques. Data lifecycle; the data scientist; machine learning; data mining; NoSQL databases; tools for storage/processing/analytics of large data set on clusters; in-data techniques.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32413D | 048 | Lecture | 3:30-6:50pm | Thursday | 55 of 57 | Goran Muric, Keith Burghardt | OHE100D | PDF (209635 KB) | |
32444D | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 34 of 50 | Seon Kim | GFS118 | PDF (250471 KB) | |
32426D | 034 | Lecture | 3:30-6:50pm | Thursday | 27 of 35 | Goran Muric, Keith Burghardt | DEN@Viterbi | PDF (209635 KB) |
Function and design of modern storage systems, including cloud; data management techniques; data modeling; network attached storage, clusters and data centers; relational databases; the map-reduce paradigm.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32401D | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 58 of 60 | Wensheng Wu | OHE132 | PDF (217996 KB) | |
32402D | 048 | Lecture | 3:30-6:50pm | Tuesday | 71 of 71 | Wensheng Wu | MHP101 | PDF (217996 KB) | |
32423D | 034 | Lecture | 4:00-5:50pm | Mon, Wed | 34 of 43 | Wensheng Wu | DEN@Viterbi | PDF (217996 KB) |
Practical applications of machine learning techniques to real-world problems. Uses in data mining and recommendation systems and for building adaptive user interfaces.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32414D | 048 | Lecture | 4:00-7:20pm | Monday | 43 of 40 | Satish Thittamaranahalli Ka | OHE100D | ||
32415D | 048 | Lecture | 12:00-1:50pm | Tue, Thu | 70 of 60 | Mohammad Reza Rajati | WPHB27 | PDF (196907 KB) | |
32416D | 048 | Lecture | 3:30-5:20pm | Mon, Wed | 60 of 50 | Mohammad Reza Rajati | SLH102 | PDF (196907 KB) | |
32443D | 034 | Lecture | 4:00-7:20pm | Monday | 21 of 30 | Satish Thittamaranahalli Ka | DEN@Viterbi | ||
32445D | 048 | Lecture | 12:00-1:50pm | Tue, Thu | 155 of 250 | Mohammad Reza Rajati | ONLINE |
Data mining and machine learning algorithms for analyzing very large data sets. Emphasis on Map Reduce. Case studies.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32418D | 048 | Lecture | 7:00-10:20pm | Tuesday | 207 of 250 | Wei-Min Shen | THH101 | Word (104815 KB) |
Function, design, and use of modern data management systems, including cloud; data management techniques; data modeling; network attached storage, clusters and data centers; relational databases; the map-reduce paradigm.
- Note: This course is only for students in the ISe analytics program. This course is not open to Data Science or CS students.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
32421R | 048 | Lecture | 3:30-4:50pm | Tue, Thu | 89 of 92 | Carl Kesselman | SLH100 | ||
32428R | 048 | Lecture | 10:00-12:50pm | Friday | 82 of 82 | Bruce Wilcox | GFS116 |
Student teams working on external customer data analytic challenges; project/presentation based; real client data and implementable solutions for delivery to actual stakeholders; capstone to degree.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
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32412D | 048 | Lecture | 1:00-4:50pm | Friday | 40 of 40 | Anna Farzindar | THH212 | PDF (307926 KB) |
Analytics for supervised and unsupervised statistical learning. Generalized linear models, discriminant analysis, support vector machines. Nonparametric classification, trees, ensemble methods, k-nearest neighbors. Principal components, clustering.
- Crosslist: This course is offered by the ISE department but may qualify for major credit in DSCI. To register, enroll in ISE 529.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
31546D | 048 | Lecture | 3:30-4:50pm | Mon, Wed | 54 of 58 | Victoria Stodden | CPA100 |
Picture archive communication system (PACS) design and implementation; clinical PACS-based imaging informatics; telemedicine/teleradiology; image content indexing, image data mining; grid computing in large-scale imaging informatics; image-assisted diagnosis, surgery and therapy.
- Crosslist: This course is offered by the BME department but may qualify for major credit in DSCI. To register, enroll in BME 528.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
29305D | 034 | Lecture | 9:00-10:50am | Tue, Thu | 9 of 10 | Brent Liu | DEN@Viterbi | ||
29310D | 048 | Lecture | 9:00-10:50am | Tue, Thu | 26 of 30 | Brent Liu | OHE100C |
Research leading to the masters degree; maximum units which may be applied to the degree to be determined by the department.
Section | Session | Units | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|---|
32432D | 048 | 1.0-6.0 | Lecture | TBA | TBA | 1 of 1 | Lizsl De Leon | OFFICE |