Spring 2014
MW 9:00 - 10:15 in MH222
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 on virtual environments in the cloud. There they will process and analyze, either on batch mode or on a real time basis 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 2 real world projects, which are the main component of the grade. Guest lectures by current practitioners are expected.
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
Peter Zadrozny is a "retired" technology executive and author of several computer science books. He has been helping the department build a curriculum in Big Data and has offered the above course several times.
MW 12:00 - 1:15 in MH222
Your laptop computer stores a large number of bits, where
each bit represents 0 or 1. A computer with N bits has 2N states,
and it is in exactly one state at any time. The computer moves from one
state to the next under control of a program.
A quantum computer has quantum bits, also called qubits. A qubit represents
0 or 1 or a “quantum superposition” of those two values. A quantum
computer with N qubits can be in any of 2N
states or in a superposition of up to 2N states, all at once!
By applying operations to its state, a quantum computer can effectively do up
to 2N operations in parallel, resulting in exponentially faster
solutions for certain problems (factoring integers is a famous example)
compared to ordinary computers. When N = 500, the number of parallel
computations is greater than the number of particles in the universe.
Nobody has a 500-qubit quantum computer yet, but these fantastic possibilities
have made quantum computing a hot area for research, funding, and even
commercial development. Lockheed Martin recently purchased D-Wave
Systems, a startup company developing and producing quantum computers.
In CS 185C / 286 we will explore quantum
computation including
·
basic quantum mechanics
·
quantum gates and circuits
·
quantum teleportation
·
quantum algorithms, including factoring and
search
·
implementing qubits
·
the course is designed to be as self-contained
as possible
·
no prior knowledge of quantum mechanics is
assumed
·
students should be comfortable with linear
algebra (Ma 129A): complex numbers, vectors, matrices, inner products,
eigenvalues, and eigenvectors.
· students should know some basic computer science: algorithms, running time analysis, big O notation.
Thomas Howell is a computer professional who has taught many courses for the CS department.
MW 1:30
- 2:45 in MH225
Making
sense of and exploiting the mass amount of available data for decision making
is a critical task for companies in many industries. This course covers the
main theories as well as widely used technologies for data mining, focusing on
simple and scalable solutions that are applicable to Big Data. You will go
through the entire Big Data mining process, from data extraction, loading and
processing to feature selection and applying machine learning models to various
mining tasks.
This course combines theories with hands-on assignments in which students are expected to work in teams to complete real-world data analytics project(s) using open source technologies (Hadoop, HDFS, Mahout, MOA, Weka) and/or commercial solutions provided by IBM (BigInsights, SystemML).
The main course components are online videos, project work, discussions of project assignments in class and guest lecturers from professionals in the field.
Students should know about
· Programming (CS046A or equivalent),
· Programming languages (at least one of the following: C, C++, Java or Perl),
· Data structures and algorithms (CS046B or equivalent).
Thanh Tran is a renowned scientist in the semantic search area with 10 years working experiences as software engineer (IBM, capgemini) and assistant professor (Karlsruhe Institute of Technology, Stanford University). He published seminal work in Semantic Search research and helped to establish an international Semantic Search community through technology benchmarking activities, tutorials and the series of workshops called SemSearch. His work is published in numerous top-tier journals and proceedings, earned prizes and a best paper award and led to successful industry collaboration with companies such as Yahoo! and IBM. He currently serves as assistant professor at San Jose State University and director of Graphinder, a technology start-up focusing on Big Data management & mining technologies for effective semantic search.
TR 6:30
- 7:45 in MH222
Game Design Studio is the capstone course in Game Design. Inter-disciplinary teams will create a substantial project over the course of the semester and present it to the public. The class will cover game production and development with groups operating as small indie-game startups. Emphasis will be placed on rapid prototyping, iteration and refinement. Lectures focus on gaming, society, and recent directions in the indie-game movement, with occasional guest lecturers from professionals in the field. Weekly activities include play-tests, prototyping and presentations. Game development will be done in Unity, or another platform with consent of instructor.
A games related course in the department of computer science or art or instructor consent.
John Pierre Bruneau is an internationally exhibiting game artist based in San Francisco. He holds a developer position at Innovation Games and has many years of experience teaching at San Jose State University as part of the Learning and Games Initiative. Bruneau cofounded Ars Virtua, The Third Faction, and the San Jose State Game Developers Club. He sees games as the epicenter of discipline convergence and the key to the future of education.
MW, 6 – 715 in ?
Introduction to the systems, design, history, and cultural
analysis of games with emphasis on development, technological literacy, markets
and impact on society. In this course we shall read about, write about, play
and design traditional paper based and video games.
None, I believe
James Morgan is a lecturer in the Art Department and faculty liaison for the Game Dev club.
CS108
(see above)
CS116B
advanced graphics (recommended for gamers)
CS134 Game Programming
CS161
Advanced Software Engineering
CS167B
This is IBM's DB2/System Z course that can substitute
for CS157B (I think). There is a high demand for DB2/Z admins.
CS155
Algorithms
CS159
Multi-core processors
CS180I
Internship (always a good idea)