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Information Technology Program (ITP)
- http://itp.usc.edu/
- After the first week of classes each semester, all classes require d-clearance to register. D-clearance instructions are available at itp.usc.edu/advisement. The 'x' designation indicates that engineering students require prior departmental approval to count 100-level and above ITP courses for major credit.
Web publishing using HTML, CSS and other Web technologies. Concepts and theory of Web site creation, page layout and production. Introduction to advanced topics.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31820R | 162 | Lecture-Lab | 4:00-6:05pm | Tue, Thu | 22 of 60 | Zune Nguyen | ONLINE | PDF (165271 KB) |  |
Introduction to Python; intended for students without prior programming experience.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31821R | 059 | Lecture-Lab | 6:00-7:05pm | Tue, Thu | 21 of 60 | Gregory Pohlner | GFS118 | PDF (215422 KB) | |
| 31822R | 059 | Lecture-Lab | 10:00-11:05am | Tue, Thu | 8 of 60 | Sinan Seymen | GFS118 | PDF (332275 KB) | |
Introductory course in computer security. Fundamentals of information security management. Threats to information integrity. Ethical hacking concerns and practice. Policies and Procedures.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31823R | 925 | Lecture-Lab | 9:00-12:10pm | Saturday | 18 of 30 | Joseph Greenfield | ONLINE | PDF (380144 KB) | |
Development of practical Python programming skills through project-based applications; "Pythonic" ways of solving problems in modern computational domains.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31824R | 059 | Lecture-Lab | 7:30-8:35pm | Tue, Thu | 9 of 60 | Gregory Pohlner | GFS118 | PDF (253639 KB) | |
Design, build, and train applied neural networks to solve real-world problems; implement neural networks for machine vision, image recognition, and object detection and tracking.
- Prerequisite: ITP 259
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31829R | 162 | Lecture | 2:00-4:50pm | MWF | 15 of 60 | Nitin Kale,Sinan Seymen | ONLINE | Word (52527 KB) | |