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Informatics (INF)
- informatics.usc.edu D class assignments for graduate students are only available on line at: myviterbi.usc.edu. Once you create your myViterbi profile, select the "D-Clearance Request Manager" to submit requests for graduate INF 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
Programming in Python for retrieving, searching, and analyzing data from the Web. Programming in Java. Learning to manipulate large data sets.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32424D | 048 | Lecture | 4:00-7:20pm | Tuesday | 11 of 40 | Yigal Arens | KAP144 | PDF (70245 KB) |   |
Threats to information systems; technical and procedural approaches to threat mitigation; policy specification and foundations of policy for secure systems; mechanisms for building secure security services; risk management. Recommended preparation: Background in computer security preferred. Recommended previous courses of study include computer science, electrical engineering, computer engineering, management information systems, and/or mathematics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32428D | 048 | Lecture | 11:00-2:20pm | Wednesday | 13 of 25 | David Morgan | OHE100C | | |
| 32429D | 034 | Lecture | 11:00-2:20pm | Wednesday | 5 of 10 | David Morgan | DEN@Viterbi | |
Application of cryptography and cryptanalysis for information assurance in secure information systems. Classical and modern cryptography. Developing management solutions. Recommended preparation: Previous degree in computer science, mathematics, computer engineering, or informatics; understanding of number theory and programming background are helpful.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32401D | 048 | Lecture | 12:00-2:30pm | Friday | 15 of 25 | Ranjan Pal | OHE136 | | |
| 32411D | 034 | Lecture | 12:00-2:30pm | Friday | 9 of 10 | Ranjan Pal | DEN@Viterbi | |
Assurance that an information system will behave as expected; assurance approaches for fielding secure information systems; case studies. Recommended preparation: Prior degree in computer science, electrical engineering, computer engineering, management information systems, and/or mathematics. Some background in computer security preferred.
- Prerequisite: INF 519
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32403D | 048 | Lecture | 1:00-4:20pm | Friday | Canceled | Clifford Neuman | | ||
| 32426R | 048 | Discussion | TBA | TBA | 0 of 25 | OFFICE | | ||
| 32413D | 034 | Lecture | 1:00-4:20pm | Friday | Canceled | Clifford Neuman | | ||
| 32432R | 034 | Discussion | TBA | TBA | 0 of 25 | DEN@Viterbi | |
Preservation, identification, extraction and documentation of computer evidence stored on a computer. Data recovery; File System Analysis; Investigative Techniques and Methodologies; Forensic Reports and Presentations.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32408D | 048 | Lecture | 9:00-10:50am | Tue, Thu | 0 of 35 | Joseph Greenfield | OHE100D | | |
| 32422D | 034 | Lecture | 9:00-10:50am | Tue, Thu | Canceled | Joseph Greenfield | |
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 |
|---|---|---|---|---|---|---|---|---|---|
| 32448D | 048 | Lecture | 10:00-11:50am | Tue, Thu | 17 of 20 | Yolanda Gil,Atefeh Farzindar | AHF145D | PDF (157913 KB) |  |
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. Recommended preparation: A basic understanding of engineering principles and programming language is desirable.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32430D | 048 | Lecture | 3:30-5:20pm | Mon, Wed | 10 of 36 | Seon Kim | KAP145 | PDF (163557 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. Duplicates credit in INF 559. Recommended preparation: INF 550 taken previously or concurrently; understanding of operating systems, networks, and databases; experience with probability, statistics, and programming.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32418D | 048 | Lecture | 10:00-11:50am | Mon, Wed | 40 of 40 | Wensheng Wu | GFS101 | PDF (236924 KB) | |
| 32431D | 048 | Lecture | 4:00-5:50pm | Mon, Wed | 21 of 40 | Wensheng Wu | THH208 | PDF (236924 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 |
|---|---|---|---|---|---|---|---|---|---|
| 32427D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 9 of 40 | Ke-Thia Yao | LVL17 | PDF (475096 KB) | |
| 32434D | 048 | Lecture | 3:30-6:50pm | Thursday | 35 of 36 | Satish Thittamaranahalli Ka | VKC261 | |
Data mining and machine learning algorithms for analyzing very large data sets. Emphasis on Map Reduce. Case studies. Recommended preparation: INF 550, INF 551 and INF 552. Knowledge of probability, linear algebra, basic programming, and machine learning.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32423D | 048 | Lecture | 10:00-11:50am | Mon, Wed | 20 of 37 | Yao-Yi Chiang,Atefeh Farzindar | VKC261 | PDF (108877 KB) |  |
| 32437D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 16 of 32 | Yao-Yi Chiang,Atefeh Farzindar | SGM226 | PDF (108877 KB) | |
| 32444D | 048 | Lecture | 5:00-8:20pm | Tuesday | 16 of 40 | Matthew Michelson | SGM601 | PDF (135432 KB) | |
Graphical depictions of data for communication, analysis, and decision support. Cognitive processing and perception of visual data and visualizations. Designing effective visualizations. Implementing interactive visualizations.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32421D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 22 of 40 | Luciano Nocera | RTH105 | PDF (352321 KB) | |
The practice of User Experience Design and Strategy principles for the creation of unique and compelling digital products and services. Recommended preparation: Basic familiarity with web development and/or graphic design using a digital layout tool.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32409R | 048 | Lecture | 2:00-4:50pm | Monday | 15 of 20 | Jaime Levy | KAP138 | PDF (170919 KB) | |
| 32417R | 048 | Lecture | 5:30-8:10pm | Monday | 4 of 20 | Jaime Levy | KAP138 | PDF (170919 KB) | |
| 32439R | 048 | Discussion | 10:00-10:50am | Tuesday | 19 of 40 | Jaime Levy | SSL150 | |
Foundations, techniques, and algorithms for building knowledge graphs and doing so at scale. Topics include information extraction, data alignment, entity linking, and the Semantic Web. Recommended preparation: Experience programming in Python.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32438D | 048 | Lecture | 2:00-5:20pm | Friday | Canceled | Craig Knoblock,Pedro Szekely | PDF (189709 KB) | |
Theory and methods of data analytics emphasizing engineering applications: multivariate statistics, supervised learning, classification, smoothing and kernel methods, support vector machines, discrimination analysis, unsupervised learning. Prerequisite: DSO 529.
- Prerequisite: DSO 529
- Crosslist: This course is offered by the ISE department but may qualify for major credit in INF. To register, enroll in ISE 529.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31529D | 048 | Lecture | 3:30-6:20pm | Friday | 11 of 20 | Cesar Acosta-Mejia | KAP134 | PDF (16684 KB) | |
Medical imaging quality, compression, data standards, workflow analysis and protocols, broadband networks, image security, fault tolerance, picture archive communication system (PACS), image database and backup.
- Crosslist: This course is offered by the BME department but may qualify for major credit in INF. To register, enroll in BME 527.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 29305D | 034 | Lecture | 9:00-11:50am | Friday | 3 of 20 | Brent Liu | DEN@Viterbi | | |
| 29310D | 048 | Lecture | 9:00-11:50am | Friday | 6 of 28 | Brent Liu | OHE100B | Word (18913 KB) | |
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.
- Restriction: Registration open to the following major(s): INF
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32449D | 048 | Lecture | TBA | TBA | 22 of 22 | OFFICE | |
Course content to be selected each semester from recent developments in informatics.
| Section | Session | Units | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|---|
| Mining the Social Web | ||||||||||
| 32425R | 048 | 4.0 | Lecture | 1:00-4:20pm | Friday | Canceled | Emilio Ferrara | PDF (3664187 MB) | | |