| Title: | Europe-Swas-Artificial-Intelligence |
| Moderator: | HERON::BUCHANAN |
| Created: | Fri Jun 03 1988 |
| Last Modified: | Thu Aug 04 1994 |
| Last Successful Update: | Fri Jun 06 1997 |
| Number of topics: | 442 |
| Total number of notes: | 1429 |
Below are descriptions of the latest PACE courses. The courses are available
throughout Europe; see the bottom of the Note for enrollment procedure.
Subject: New PACE AI course Descriptions E304E-E305E-E306E
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Subject: EY-E304E - PACE ANNOUNCEMENT - NATURAL LANGUAGES SYSTEMS
COURSE SUMMARY & CHARACTERISTICS : EXPERT SYSTEMS/ARTIFICIAL INTELLIGENCE
COURSE TITLE : EY-E304E-P0 NATURAL LANGUAGE SYSTEMS Duration : 8 HOURS
LOCATION : ALL EUROPEAN OPEN LEARNING CENTRES ON REQUEST
Course type : Self-paced, with PACECOM notesfile interaction with Lecturers.
Target functions : EIS, Engineering, Manufacturing
*******************************************************************
Could you please forward the following EUROPEAN PACE ANNOUNCEMENT
through your appropriate channels.
-------------------------------------------------------------------------------
NATURAL LANGUAGE SYSTEMS
TARGET AUDIENCE
Managers with an interest in the state of the art and the application
potential of natural language systems, system designers and programmers
who are considering to build a natural language system, specialists in
software ergonomics.
Students in computer science, information science, cognitive psychology
of the computational approaches to natural language.
COURSE OBJECTIVES
The course presents the fundamental concepts and techniques used in
current natural language systems.
The course objectives are:
- To demonstrate the application potential of natural language systems
- To examine the range of existing systems and their strengths and
limitations
- To characterise the state of the art in natural language processing
- To point out essential problems and proposed strategies for solving
them.
In an economy based on the generation and dissemination of information,
natural language systems can have two important positive impacts:
1. They can make computer applications available to segments of the
population that are unable or unwilling to learn a formal language;
2. They can increase knowledge productivity in providing automatic
means for manipulating knowledge expressed in natural language. Natural
language systems are a prerequisite for advanced knowledge based systems
since the ability to acquire, retrieve, exploit and present knowledge
critically depends on natural language comprehension and production.
They are becoming increasingly important for such applications as
intelligent interfaces to databases, expert systems and vision systems.
COURSE OUTLINE
1. Introduction :
Natural Language Systems as Knowledge-Based Systems - Wolfgang Wahlster
Knowledge Sources and Processing Phases
Application of Natural Language Systems: A First Overview
Architecture of Natural Language Systems
2. Grammar Models for Natural Language Systems - Hans Uszkoreit
Phrase Structures and Feature Structures
Unification Grammars
Relevant Grammar Theories, Formalisms, and Implementations
Local and Non local Dependencies
Problems of Word Order
The Integrated Representation of Lexicon, Syntax and Semantics
3. Syntactic and Morphological Processing - Hans Uszkoreit
Lexicon and Lexical Access
Morphological Processing
Parsing Strategies
4. Semantic Processing Techniques - Hans Uszkoreit & Wolfgang Wahlster
Lexical Semantics
Modeltheoretic Semantics and Discourse Representations
Semantic Representation Languages and Situation Schemata
5. Cooperative Response Generation - Wolfgang Wahlster
Techniques for Over-Answering
Building and Exploiting User Models
The Role of Discourse Models
6. Interactive Natural Language Systems: Application, Products and
Prototypes - Wolfgang Wahlster
Natural Language Interfaces to Database Systems
Natural Language Access to Expert Systems
Intelligent Help Systems
Natural Language Access to Vision Systems
Multimodal Systems as Intelligent Interfaces
The Anatomy of Dialogue System
SUPPORT MATERIAL FORESEEN
LECTURERS
Hans Uszkoreit - U. Saarbruecken
Wolfgang Wahlster - U. Saarbruecken
- DATE: MID MAY 1990
- LOCATION : PACE - SELF PACED TRAINING AVAILABLE IN
ALL EUROPEAN OPEN LEARNING CENTRES ON REQUEST
- ENROLMENT PROCEDURE :
-------------------
All enrolment request MUST BE SENT to LOCAL OLC MANAGER with
the following information :
Course Corporate Nbr :EY-E304E-P0
Course Title :NATURAL LANGUAGE SYSTEMS
:
Course Location : .......
Complete Student name : <>
*** PREREQUISITE *** : YES or NO
Function : <>
Exact Job title : <>
Badge number : <>
Cost centre : <>
VAXmail or DECmail Addr.: <>
Manager's Name : <>
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Subject: EY-E305E - PACE ANNOUNCEMENT - NEURAL NETWORKS INTRODUCTION
COURSE SUMMARY & CHARACTERISTICS :EXPERT SYSTEMS/ARTIFICIAL INTELLIGENCE
COURSE TITLE : EY-E305E-P0 NEURAL NETWORKS - INTRODUCTION
Duration : 6 HOURS
Course type : Self-paced, with PACECOM notesfile interaction with Lecturers.
LOCATION : ALL EUROPEAN OPEN LEARNING CENTRES ON REQUEST
Target functions : EIS, Engineering, Manufacturing
*******************************************************************
Could you please forward the following EUROPEAN PACE ANNOUNCEMENT
through your appropriate channels.
--------------------------------------------------------------------
NEURAL NETWORKS - INTRODUCTION
TARGET AUDIENCE
R and D staff and application engineers.
Graduate students in Artificial Intelligence and research scientists
in Computer Science.
COURSE OBJECTIVES
The course covers the recently emerged field of neural networks. In
the introductory course, it provides a detailed introduction to the main
principles and methods of neuro-computing. The advanced course planned
for the Fall 1990 goes into detailed presentation of the techniques
for building and using neural networks in practical applications.
It presents the major learning algorithms, the software and hardware
tools presently available on the market. It reviews the major potential
industrial applications, and illustrates the presentation with detailed
case studies.
COURSE OUTLINE
1. Introduction:
Neural network methods compared to Symbolic methods, Artificial and
natural neural networks.
2. Automata theory:
Definitions and various classes of automata
3. Learning:
Supervised learning: adaline, perceptron, multi layer networks
Unsupervised learning: topological maps algorithms
4. Applications:
Supervised learning: speech and image recognition
Unsupervised learning: speech recognition
Overview of major industrial applications.
SUPPORT MATERIAL FORESEEN
LECTURERS
Francoise Fogelman studied Mathematics and Computer Science at the University of
Paris VI and the Ecole Normale Superieure. In 1986, she joined the Laboratory of
Artificial Intelligence at EHEI (University of Paris V) where she created a team
on neural networks. The team has moved to LRI (University of Paris XI) in July
1989. The team has about 15 researchers. It is currently engaged in fundamental
research on neural algorithms, their links with Data ANalysis and Artificial
Intelligence techniques. It is also involved in the development of real-sized
applications through active collaborations with industrial partners. It
participates in various international (ESPRIT) and national (MRES, DRET, CNRS)
projects. It has provided a training curriculum in Neural Nets for graduate
level and for various industrial seminars, for about 4 years.
INSTITUTION
Universite de Paris
- DATE: END OF MAY 1990
- LOCATION : PACE - SELF PACED TRAINING AVAILABLE IN
ALL EUROPEAN OPEN LEARNING CENTRES ON REQUEST
- ENROLMENT PROCEDURE :
-------------------
All enrolment request MUST BE SENT to LOCAL OLC MANAGER with
the following information :
Course Corporate Nbr :EY-E305E-P0
Course Title :NEURAL NETWORKS - INTRODUCTION
:
Course Location : .......
Complete Student name : <>
*** PREREQUISITE *** : YES or NO
Function : <>
Exact Job title : <>
Badge number : <>
Cost centre : <>
VAXmail or DECmail Addr.: <>
Manager's Name : <>
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Subject: EY-E306E - PACE ANNOUNCEMENT - NEURAL NETWORKS ADVANCED
COURSE SUMMARY & CHARACTERISTICS : EXPERT SYSTEMS/ARTIFICIAL INTELLIGENCE
COURSE TITLE : EY-E306E-P0 NEURAL NETWORKS - ADVANCED
Duration : 12 HOURS
Course type : Self-paced, with PACECOM notesfile interaction with Lecturers.
LOCATION : ALL EUROPEAN OPEN LEARNING CENTRES ON REQUEST
Target functions : EIS, Engineering, Manufacturing
*******************************************************************
Could you please forward the following EUROPEAN PACE ANNOUNCEMENT
through your appropriate channels.
--------------------------------------------------------------------
NEURAL NETWORKS - ADVANCED
TARGET AUDIENCE
R and D staff and application engineers.
Graduate students in Artificial Intelligence and research scientists
in Computer Science.
COURSE OBJECTIVES
The course covers the recently emerged field of neural networks. In the
introductory course, it provides a detailed introduction to the main principles
and methods of neuro-computing. The advanced course planned for Fall 1990 goes
into detailed presentation of the techniques for building and using neural
networks in practical applications. It presents the major learning algorithms,
the software and hardware tools presently available on the market. It reviews
the major potential industrial applications, and illustrates the presentation
with detailed case studies.
In the advanced course, to give the necessary basis for in-depth understanding
of neural algorithms. To present the industrial potential of the technology. To
give the tools to design a working neural net application.
COURSE OUTLINE
1. Introduction:
Complements to introduction of introductory course: knowledge reprsentation
development of neural network technologies in the world (US, Japan, Europe).
2. Automata theory:
Complements to introduction of introductory course: dynamics of neural
networks.
3. Adaptive systems
Linear separators: adaline, madaline, perceptron
Associative memories: linear (Kohonen), Brain State in the Box (Anderson),
threshold (Hopfield), Bidirectional Associative Memories (Kosko).
Limits of adaptive systems.
4. Learning
Complements to introduction of introductory course: comparison of
network learning and symbolic learning (Machine learning)
The generalization problem (after specific learning: generalize to new
examples)
5. Multi layer networks
Complements to introduction of introductory course: derivation of
the Gradient
Back Propagation algorithm, extensions (momentum, decay and shared
weights).
Links with data analysis.
How to desing a network for your application ?
Case studies of typical applications:
- image processing
- speech processing: recognition, noise reduction
- signal processing: radar, sonar
6. Topological maps
Complements to introduction of introductory course: modified version
of topological map algorithm
Applications in combinatorial optimization:
- travelling salesman problem: comparison with other neural algorithms
(elastic net, elastic matching, Hopfield's net).
- image matching
7. Other models
Simulated annealing
Boltzman machine
Adaptive resonance theory, counterpropagation
8. Neural computers: hardware and software
Software tools
- simulators: overview of commercial products
- neural languages
Hardware
- neuro-computers
- neural chips
- optical devices
9. Industrial applications
When and why to use a neural approach
Overview of present applications
R & D programs in the world
Industrial perspectives and future developments
10. Conclusion
Summary of major techniques for building a Neural Net-based application.
SUPPORT MATERIAL FORESEEN
LECTURERS
Francoise Fogelman - U. Paris
INSTITUTION
Universite de Paris
- DATE: SEPTEMBER 1990
- LOCATION : PACE - SELF PACED TRAINING AVAILABLE IN
ALL EUROPEAN OPEN LEARNING CENTRES ON REQUEST
- ENROLMENT PROCEDURE :
-------------------
All enrolment request MUST BE SENT to LOCAL OLC MANAGER with
the following information :
Course Corporate Nbr :EY-E306E-P0
Course Title :NEURAL NETWORKS - ADVANCED
:
Course Location : .......
Complete Student name : <>
*** PREREQUISITE *** : YES or NO
Function : <>
Exact Job title : <>
Badge number : <>
Cost centre : <>
VAXmail or DECmail Addr.: <>
Manager's Name : <>
| T.R | Title | User | Personal Name | Date | Lines |
|---|---|---|---|---|---|
| 183.1 | Complete List | DOAR::TURNER | MALLET::TURNER or DTN 768-5411 | Fri Mar 02 1990 18:46 | 232 |
Below is the latest complete list of PACE courses; a number of them
should be a good match for requests we've had.
................................................................
From: NAME: Nick MEYER @GEO
FUNC: OLC TRNG, IVIS, PACE,DVN
TEL: DTN 893-3111 <MEYER AT GVA02A1 @EHQMTS @GEO>
To: TURNER@SPYDER@VAXMAIL
From: NAME: Nick MEYER @GEO
FUNC: OLC TRNG, IVIS, PACE,DVN
TEL: DTN 893-3111 <MEYER AT GVA02A1 @EHQMTS @GEO>
Date: 31-Jan-1990
Posted-date: 31-Jan-1990
Precedence: 1
Subject: (A) New PACE AI courses, needing promotion & Feedback
To: MARK TURNER @BST
CC: JIM KANE @VBO
Hello Mark,
As you know there is a whole slew of new PACE courses on AI
that have just been announced.
I would be grateful if you could announce & Promote these
in your AI notes file, or the AI Competency circle notes file or wherever
you think (hopefully) they would do most good.
I also need to do a presentation to the EIS T&D board on
March 15th, & I would be grateful if you could give me some inputs on which
PACE courses you would recommend as being very suitable for EIS & why.
I have attached the list of courses that are available
during FY90, & will send the course descriptions by
separate mail..
Looking forward to your feedback,
Nick(M)
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Date: 19-Jan-1990 04:30pm CET
From: Nick MEYER @GEO
MEYER
Dept: OLC TRNG, IVIS, PACE,DVN
Tel No: DTN 893-3111
Doc No: 016638
TO: See Below
Subject: I. PACE Courses,second Semester update, for FY90
Greetings,
Here are the latest updates to the Pace course offerings.
I have underlined the EY number where there have been updates on start of
broadcasts, additions & deletions.
New Courses & descriptions should announced during week of
January 22nd.
The latest PACE broadcast schedule (starting on Feb 5th) is
for you all to see in PortaCom, right now.
PACE Course offerings for the Spring 1990 Semester. (rev 4.0)
===============================================
EY-xxxxE-PO PACE # TITLE
or B'cast date.
LIVE (& Interactive) BROADCASTS
===============================
EY-E321E-PO October 12th Live Broadcast from Manchester Polytech.
"Technology Management Forum"
EY-E320E-PO November 7th Live update & Question & Answer session
on the" Techniques for Real time software
design" course.
EY-E313E-PO November 23rd OPEN FORUM: Live Broadcast on Advanced
Manufacturing topics, MAP, EMUG, Map
Products & Map Applications .2hrs
with Klaus Grund of EDS.
EY-E322E-PO November 30th Large scale event from the ESPRIT IT
forum in Brussels, with Currien, Agnelli
Davignon, Duer, etc...
=========== December 19th Live update on & Question & Answer session
on "Techniques for Real Time Software design"
***This Broadcast was cancelled *********
EY-E324E-PO December 21st Open Forum: Closing session on Autumn
PACE Courses.
Note: New set of live broadcsat to start in March to be announced in late
January.
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EXPERT SYSTEMS & ARTIFICIAL INTELLIGENCE:
=========================================
EY-E280E-PO ES/AI-01 Synopsis of Autumn School on Expert Systems:
(includes 4 courses below)
EY-E279E-PO ES/AI-01A Crucial Question Overview (8hrs, Oct.89)
EY-E278E-PO ES/AI-01B Knowledge Acquisition & Learning (4hrs,Nov 89)
EY-E277E-PO ES/AI-01C Practical tools for Automated Learning &
Maintenance, (4hrs, Jan 90)
EY-E281E-PO ES-AI-01D Real Time Expert Systems. (4 hrs,early 1990)
EY-E282E-PO ES/AI-02 Self Organisation & Neural Nets, Cognition
and Artificial Intelligence (5hrs, 12/89)
EY-E283E-PO ES/AI-03 Relating Task features to Expert Systems
Solutions (4hrs, Nov 89)
EY-E261E-PO ES/AI-LPP1 Prolog,Logic Programming & Expert Systems.
(20hrs, Oct 89)
EY-E304E-P0 ES/AI-04 Natural Languages Systems( 8 hrs)
=========== (mid May 90)
EY-E305E-P0 ES/AI-05A Neural Networks: Introduction (6hrs)
=========== (end of May 90)
EY-E306E-P0 ES/AI-05B Neural Networks: Advanced (12hrs)
=========== (September 90)
EY-E317E-PO ES/AI-06 Advanced AI Programming using LISP
=========== (12hrs, March 90)
EY-C347E-PO ES/AI-FP14 Knowledge Engineering (16hrs)(March 90)
Introduction to Expert Systems.
-0-0-0-
TELECOMMUNICATIONS:
===================
EY-E284E-PO TC-01 OSI- Open Systems Interconnect (15hrs, Oct89)
EY-E307E-P0 TC-02 ISSSE'89 : International Symposium on
=========== Signals, Systems & Electronics, Erlangen
(6hrs, Nov89)
EY-E308E-P0 TC-03 Optical Fibers & Networks (30hrs)
=========== (4hrs in Feb, 14hrs in May, 12hrs in Sept 90)
EY-E309E-P0 TC-04 ISDN II (10hrs starting March 23rd)
===========
-0-0-0-
SOFTWARE ENGINEERING
====================
EY-E287E-PO SE-01 Techniques for real time software design
(12hrs, starting Oct.89)
EY-E288E-PO SE-03 Summer School on Software Engineering in
ESPRIT (12hrs, starting Oct 3rd, '89)
EY-E310E-P0 SE_04 Introduction to formal specification
=========== techniques.(6 hrs, June 90 )
EY-E311E-P0 SE-05 The Z Notation method (10hrs, Autumn 90)
===========
EY-E312E-P0 SE-06 Software quality metrics & testing (9hrs)
=========== (February 90)
-0-0-0-
ADVANCED MANUFACTURING TECHNIQUES:
==================================
EY-E276E-PO AMT-03 World class production in a global economy
measuring up to the tasks ahead. (2hrs,Nov89)
EY-E313E-P0 MAP Open Forum on Manufacturing Protocol (2hrs)
=========== Live Broadcast of Nov 23rd, 1989.
EY-E314E-P0 AMT-02 Elements of Adv. Manuf Technologies (28hrs)
=========== (8hrs in Feb, 8hrs in Mar, 4hrs in May,
8hrs in June)
-0-0-0-
MICROELECTRONICS & VLSI:
=======================
EY-E285E-PO ME-01 The GaAS MMIC Foundry: How to use it.
(8HRS, starting OCT.89)
EY-E286E-PO ME-03 OPTOELECTRONICS (10hrs, starting Nov 89)
EY-E323E-PO ME-02 Technology Evaluation of III-V integrated
=========== circuits: Construction & Electrical failure
analysis. (3hrs, 5th Feb 90)
EY-E315E-P0 ME-04 Analogue Design (8hrs starting 19th Feb 90)
===========
-0-0-0-
TECHNOLOGY MANAGEMENT
=====================
EY-E275E-PO TM-01 International Forum on Technology
Management (21hrs, starting Oct 4th, 1989)
EY-E316E-P0 TM02 TECHNOLOGY STRATEGY (10hrs, 13th March 90)
=========== Now includes (what was TM03):
Strategic Alliances: joint ventures &
=========== acquisitions, determinants of success.
EY-E318E-P0 TM04 Planning & Executing Complex Projects (5hrs)
=========== (end of April 90)
EY-C358E-PO TM-FP61 Project Management (5hrs, Feb 90)
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