Course Demos: Computer Science
Online course lectures utilize the Flash player to distribute content. Video of the instructor is delivered as a Flash streaming FLV file. Lecture slides are captured and delivered as SWF files. Audio-only selections are also offered. The Flash player is required.
Lecture slides are synchronized with the video/audio. Lectures can be navigated through thumbnails of the slides that will jump you to different points in the lecture. I2CS lectures can be viewed on Windows, Mac OS, and Linux.
The sample lectures below represent a handful of the courses that we offer. Lecture capture is automated, so there may be a minute or so where the professor is talking to students, but you won't be able to hear anything. Use the thumbnails to navigate to a later point in the lecture. All of the sample lectures below have audio.
CS 512: Advanced Data Mining
- View CS 512 Lecture
Course Description: An advanced course on principles and algorithms of data mining. Data cleaning and integration; descriptive and predictive mining; mining frequent, sequential, and structured patterns; clustering, outlier analysis and fraud detection; stream data, web, text, and biomedical data mining; security and privacy in data mining; research frontiers.
Prerequisites: CS 412
CS 463: Computer Security II
- View CS 463 Lecture
Course Description: Program security, trusted base, privacy, anonymity, non-interference, information flow, confinement, advanced auditing, forensics, intrusion detection, key management and distribution, policy composition and analysis, formal approaches to specification and verification of secure systems and protocols, and topics in applied cryptography. Same as ECE 424. 3 undergraduate hours. 3 or 4 graduate hours.
Prerequisites: CS 461
Recommended: CS 475
CS 543: Computer Vision
- View CS 543 Lecture
Course Description: This course examines information processing approaches to computer vision, algorithms, and architectures for artificial intelligence and robotics systems capable of vision. Three-dimensional properties of a scene from its images, such as distance, orientation, motion, size and shape, acquisition, and representation of spatial information for navigation and manipulation in robotics are covered as well.
Prerequisites: Undergraduate degree and a course in data structures (such as CS 225).