collapse allexpand all
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 |
|---|---|---|---|---|---|---|---|---|---|
| 32401D | 048 | Lecture | 5:00-7:20pm | Tuesday | 19 of 40 | Jeremy Abramson | KAP164 | PDF (95225 KB) |   |
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 |
|---|---|---|---|---|---|---|---|---|---|
| 32421D | 048 | Lecture | 6:40-9:20pm | Thursday | Canceled | | |||
| 32431D | 034 | Lecture | 6:40-9:20pm | Thursday | Canceled | |
Assurance as the basis for believing an information system will behave as expected. Approaches to assurance for fielding secure information systems that are fit for purpose. Recommended preparation: Prior degree in computer science, electrical engineering, computer engineering, management information systems, and/or mathematics. Some background in computer security preferred.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32423D | 048 | Lecture | 6:40-9:20pm | Wednesday | 22 of 25 | Clifford Neuman | OHE120 | | |
| 32433D | 034 | Lecture | 6:40-9:20pm | Wednesday | 12 of 25 | Clifford Neuman | 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: INF 522. Recommended preparation: Prior degree in computer science, mathematics, computer engineering, or informatics; advanced knowledge of computer architecture, operating systems, and communications networks will be valuable.
- Prerequisite: INF 522
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32416D | 048 | Lecture | 5:00-7:20pm | Tuesday | 17 of 30 | Tanya Ryutov | KAP146 | |
Preservation, identification, extraction and documentation of computer evidence stored on a computer. Data recovery; cryptography; types of attacks; steganography; network forensics and surveillance. Recommended preparation: Previous degree in computer science, mathematics, computer engineering, or informatics; a working understanding of number theory and some programming knowledge will be helpful.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32408D | 048 | Lecture | 12:30-1:50pm | Tue, Thu | 15 of 30 | Joseph Greenfield | OHE120 | | |
| 32438D | 034 | Lecture | 12:30-1:50pm | Tue, Thu | 10 of 12 | Joseph Greenfield | DEN@Viterbi | |
Fundamental concepts in information security and privacy; Security and privacy policies, threats, and protection mechanisms; Security and privacy laws, regulations, and ethics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32412D | 048 | Lecture | 12:00-2:50pm | Friday | 14 of 40 | Clifford Neuman | OHE100C | | |
| 32413D | 034 | Lecture | 12:00-2:50pm | Friday | 8 of 10 | Clifford Neuman | DEN@Viterbi | |
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 |
|---|---|---|---|---|---|---|---|---|---|
| 32406D | 048 | Lecture | 11:00-12:20pm | Tue, Thu | 11 of 25 | Yolanda Gil | SOSB41 | PDF (182426 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. 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 |
|---|---|---|---|---|---|---|---|---|---|
| 32405D | 048 | Lecture | 3:30-4:50pm | Mon, Wed | Canceled | Seon Kim | PDF (135967 KB) | | |
| 32411D | 048 | Lecture | 8:30-9:50am | Mon, Wed | 23 of 50 | Wensheng Wu | GFS116 | PDF (198089 KB) | |
Practical applications of machine learning techniques to real-world problems. Uses in data mining and recommendation systems and for building adaptive user interfaces. Recommended preparation: INF 550 and INF 551 taken previously or concurrently; knowledge of statistics and linear algebra; programming experience.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32402D | 048 | Lecture | 2:00-4:50pm | Wednesday | 34 of 37 | Stefan Scherer | WPH207 | PDF (86884 KB) | |
| 32410D | 048 | Lecture | 3:30-6:20pm | Thursday | 34 of 37 | Satish Thittamaranahalli Ka | KAP146 | |
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 |
|---|---|---|---|---|---|---|---|---|---|
| 32403D | 048 | Lecture | 11:00-12:20pm | Tue, Thu | 10 of 42 | Wensheng Wu | GFS207 | PDF (168795 KB) | |
| 32414D | 048 | Lecture | 10:00-11:50am | Mon, Wed | 31 of 40 | Yao-Yi Chiang,Atefeh Farzindar | KAP158 | PDF (111236 KB) | |
| 32426D | 048 | Lecture | 2:00-3:20pm | Tue, Thu | 13 of 40 | Wensheng Wu | VHE217 | PDF (168795 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 |
|---|---|---|---|---|---|---|---|---|---|
| 32404D | 048 | Lecture | 1:00-3:50pm | Friday | Canceled | |
Understand and apply user interface theory and techniques to design, build and test responsive applications that run on mobile devices and/or desktops. Recommended preparation: Knowledge of data management, machine learning, data mining, and data visualization.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32427D | 048 | Lecture | 5:00-6:20pm | Mon, Wed | 27 of 30 | Amir Soheili | GFS222 | |
The practice of User Experience Design and Strategy principles for the creation of unique and compelling digital products and services.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32428R | 048 | Lecture | 5:00-7:50pm | Monday | 19 of 20 | Jaime Levy | VKC161 | PDF (175593 KB) | |
| 32436R | 048 | Lecture | 2:00-4:50pm | Monday | 19 of 20 | Jaime Levy | VKC161 | PDF (175593 KB) | |
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. Recommended preparation: Knowledge of data management, machine learning, data mining, and data visualization.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 32429D | 048 | Lecture | 3:00-5:50pm | Friday | 8 of 40 | Atefeh Farzindar | KAP163 | PDF (411325 KB) | |
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. Prerequisite: BME 425 or BME 525 and BME 527.
- Prerequisite: 1 from (BME 425 or BME 525) and BME 527
- Crosslist: This course is offered by the BME department but may qualify for major credit in INF. To register, enroll in BME 528.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 29305D | 034 | Lecture | 9:00-11:50am | Friday | Canceled | Brent Liu | | ||
| 29310D | 048 | Lecture | 9:00-11:50am | Friday | Canceled | Brent Liu | |
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 | Units | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|---|
| 32448D | 048 | 1.0-6.0 | Lecture | TBA | TBA | 17 of 30 | Art Perez | OFFICE | | |
| 32449D | 048 | 2.0 | Lecture | TBA | Canceled | | ||||
| TBA | OFFICE |