NEW MASTERS PROGRAM IN KNOWLEDGE DISCOVERY AND DATA MINING

[Sebastian Thrun]

Carnegie Mellon, Center for Automated Learning & Discovery announces:

A NEW MASTERS PROGRAM IN KNOWLEDGE DISCOVERY AND DATA MINING

The extraordinary spread of computers and online data is changing
forever the way that important decisions are made in many
organizations.  Hospitals analyze online medical records to decide
which treatments to apply to future patients. Banks routinely analyze
past financial records to learn to spot future fraud.  Today's demand
for data mining expertise far exceeds the supply, and this imbalance
will become more severe over the coming decade.

To educate the next generation of experts in this important area,
Carnegie Mellon University offers a new Master's program in Knowledge
Discovery and Data Mining (KDD).  This new inter-disciplinary program
trains students to become tomorrow's leaders in the rapidly growing
area of Knowledge Discovery and Data Mining.  It is offered by
Carnegie Mellon's Center for Automated Learning and Discovery (CALD),
which has assembled a large multi-disciplinary team of faculty and
students across several academic departments.

KDD candidates will be trained in all important areas related to
scientific data mining and knowledge discovery. The Master's program
balances interdisciplinary course work, hands-on project work, and
cutting-edge research carried out under direct faculty supervision. 
The curriculum addresses areas such as advanced machine learning 
algorithms, statistical principles and foundations, database
and data warehousing methods, complexity analysis, approaches to data
visualization, privacy and security, and specific application areas
such as business, marketing, finance, and public policy.  Our
graduates are uniquely positioned to pioneer new data mining and
knowledge discovery efforts, and to pursue top notch research on the
next generation of data mining tools, algorithms, and systems.

Carnegie Mellon invites applications of qualified individuals.
Admission is highly competitive. A limited number of fellowships are
available, which will be provided on a competitive basis. The
application deadline is February 5, 2000.

For more details about the program or to apply:
    http://www.cs.cmu.edu/~kdd