chucko@saturn.ucsc.edu (Chuck Stein) (06/11/88)
The University of California
Eighteenth Annual
INSTITUTE IN COMPUTER SCIENCE
presents courses in:
* Scientific Visualization * Fault Tolerant Computing
* Parallel Computation * Image Engineering
* Data Compression * Machine Learning
at
Techmart, Santa Clara
and
on campus in Santa Cruz
Following is a course description for:
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Expert Systems and Artificial Neural Systems:
Technology, Prototyping, Development and Deployment
in the Corporate Environment
July 13-15
Instructor: TOM J. SCHWARTZ, MSEE, MBA.
X421 Computer Engineering (2)
For programmers, engineers, engineering managers, and corporate
technology managers. This course will introduce participants to two of
today's most advanced computing technologies for the corporate
environment: expert systems and artificial neural systems. It will
prepare the attendees to evaluate the technology and current
commercial product offerings; to choose appropriate problems to which
the technology can be applied; to gain program support from
management; to complete a prototype; to compose the project plan and
to see the project through from system development to deployment.
Overview
The course presents a systematic introduction to the strategic use of
expert systems and artificial neural systems within the corporate
project environment, from technology introduction and history through
project plan, prototype, project development and deployment. Founded
on the concept that new technology never replaces old technology (it
merely reconfigures it), the course will focus on introducing these
technologies within the context of current methods and products. A
clear focus on productivity and improvement of the bottom line is the
goal.
Recently both expert systems and artificial neural systems have been
receiving tremendous attention as cutting edge technologies capable of
enhancing existing products and offering means to solve complex
problems which have defied conventional technology. Both
technologies offer the ability to distribute knowledge and expertise.
Expert systems require the human articulation of knowledge which is
captured in an expert system. Artificial neural systems can extract
knowledge from example sets. The course will also examine the
possibilities of merging these technologies together and integrating
them into a firm existing technology base.
Wednesday
Morning: Overview of Artificial Intelligence and Expert Systems.
This will cover definitions and composition, history, philosophical
foundations, and the "Great Schism" between expert systems and
artificial neural systems. This will be followed by an introduction to
expert systems, the basics of knowledge representation and control
structure, the Language-Shell Continuum and methods of control.
Afternoon: Introduction to Artificial Neural Systems and Generic
Technology Issues. This section will consists of an introduction to
artificial neural systems basics of supervised and unsupervised
learning and the modeling continuum. We will then consider the
common considerations of both technologies including: I/O, basics of
problem selection, hardware, "Hooks, Hacks & Ports", validation issues
and the "Explanation Debate".
Thursday
Morning: This section will cover areas where these technologies have
succeeded and failed in the areas of diagnostics, planning, pattern
recognition, and the extraction of knowledge from data.
Afternoon: Project Selection: In this section attendees will have the
opportunity to examine what they have learned and select a proposed
project. During the rest of the course, each person will be able to
match that selection with the other issues and complete an initial
project plan. Issues to be examined will include winning management
support, development strategies, deployment strategies, and budgeting.
Friday
Morning: Planning for Change: At this time, attendees will examine the
impact existing environment, hardware, software, cultural, business,
stake holders, and legal considerations will have on their selected
project. After this, we will examine a project plan and consider the
question of "what constitutes success, and what is its impact?"
Afternoon: Build or buy, vendor selection and wrap-up: For the final
session, we will consider the "build or buy" issue and available
software and hardware. There will be a summary of current available
hardware, languages, and tools. Also examined will be the use of
consultants. This will be followed by a course summary with time for
further questions and comments.
Instructor: TOM J. SCHWARTZ, MSEE, MBA, is the founder of Tom
Schwartz Associates of Mountain View, California.
Fee: Credit, $895 (EDP C6035)
Dates: Three Days, Wed.-Fri., Jul. 13-15, 9 a.m.-5 p.m.
Place: Techmart, 5201 Great America Pkwy., Santa Clara
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RESERVATIONS:
Enrollment in these courses is limited. If you wish to attend a course
and have not pre-registered, please call (408) 429-4535 to insure that
space is still available and to reserve a place.
DISCOUNTS:
Corporate, faculty, IEEE member, and graduate student discounts and
fellowships are available. Please call Karin Poklen at (408) 429-4535
for more information.
COORDINATOR:
Ronald L. Smith, Institute in Computer Science, (408) 429-2386.
FOR FURTHER INFORMATION:
Please write Institute in Computer Science, University of California
Extension, Santa Cruz, CA 95064, or phone Karin Poklen at (408) 429-
4535. You may also enroll by phone by calling (408) 429-4535. A
packet of information on transportation and accommodations will be sent
to you upon receipt of your enrollment.