Every
semester the CS Department offers a selection of experimental courses on
interesting topics and taught by interesting people. All of these courses can be
used as elective credit for the BSCS and MSCS degrees (don't know about the
BSSE degree).
Section 2
Time: MW 9:00 – 10:15
Room: MH 222
Instructor: P. Zadrozny
This course will have a very practical focus on the techniques and tools for capturing, storing, processing and analyzing big data. Tools such as Hadoop and Splunk will be used in virtual, cloud-based environments. There they will process and analyze, either in batch mode or real time, big data that will range from web log files to twitter and other specialized data.
This is a hands-on course in which students are expected to work in teams to complete at least 2 real world projects, which are the sole components of the grade. Guest lectures by current practitioners are expected.
Prerequisites:
CS 146 – Data Structures and Algorithms
CS 157A – Introduction to Data Base Management Systems
With a “C-“ grade or better in each, or instructor consent
Section 3
Time: T, Th 10:30 – 11:45
Room: MH223
Instructor: M. Cheng
Employers complain that CS graduates don't have sufficient understanding of the business context of the code they write. This course is your chance to stand above the competition. It would also be excellent background for thise contemplating starting their own businesses.
Section 4
Time: T, Th 16:30 – 17:45
Room: MH223
Instructor: J. Finder
Back by popular demand, this course, along with section 5, are part of the evolving Game Studies curriculum.
Section 5
Time: MW 1830 – 1945
Room: Art 135
Instructor: James Morgan
Introduction to the systems, design, history, and cultural analysis of games with emphasis on critical studies, development, technological literacy, markets and impact on society. Prerequisite: Upper division standing or instructor consent.
Section 1
Time: MW 900 - 1015
Room: MH225
Instructor:
David Taylor
Game theory has ties into many fields: economics, politics,
society, policy, and, sometimes even games. In this course, we will
take a brief survey of the field with extra time spent on algortihmic
aspects.
-Game Theory: A quick introduction to general game theory, beyond the
prisoner's dilemma.
-Mechanism Design: How to set up system rules such that, when players
act in their own self-interest, it helps the system as a whole.
-Inefficiency of Greed: We will get some idea of why regulation isn't
exactly the stifling factor it is sometimes made out to be politically.
Prerequisites: Graduate standing or a strong algorithm background and
instructor consent.