Received: from CS.CMU.EDU by A.GP.CS.CMU.EDU id aa00417; 12 Jun 95 11:40:04 EDT Received: from sun3.nsfnet-relay.ac.uk by CS.CMU.EDU id aa18219; 12 Jun 95 11:39:39 EDT Received: from orac.sunderland.ac.uk by sun3.nsfnet-relay.ac.uk with JANET SMTP id ; Mon, 12 Jun 1995 16:39:20 +0100 Received: from missgate2.sunderland.ac.uk (uk.ac.sunderland.miss) by orac.sund.ac.uk; Mon, 12 Jun 1995 16:38:42 +0000 Received: by missgate2.sunderland.ac.uk with Microsoft Mail id <2FDCD1BE@missgate2.sunderland.ac.uk>; Mon, 12 Jun 95 16:46:06 PDT From: KENDAL Simon To: aipredoc Subject: course: Knowledge Engineering @ University of Sunderland (England) Date: Mon, 12 Jun 95 16:45:00 PDT Message-Id: <2FDCD1BE@missgate2.sunderland.ac.uk> Encoding: 92 TEXT X-Mailer: Microsoft Mail V3.0 content-length: 3191 Sender: ai@A.GP.CS.CMU.EDU Course: M.Sc. Knowledge Engineering ================================= This is an ADVANCED masters course intended for graduates who have either a computing degree or relevent experience, based at the University of Sunderland in the United Kingdom. Objectives ========= On completion of this course the student will be able to: # understand the nature, role and function of knowledge based systems in organisations # elicit and represent knowledge from a specified problem domain # specify, design, implement and document knowledge based systems which are technically, professionally and economically acceptable # exhibit sufficient critical awareness of current knowledge based technologies to be able to select appropriate areas for KBS deployment # select and critically assess relevant material from original papers and articles, in order to plan, schedule, monitor and control the conduct of a substantial piece of research and development work culminating in the production of a knowledge based system # communicate, both orally and in writing, a programme of work in knowledge engineering # act as a professional knowledge engineer with respect to codes of conduct and practice Course Overview =============== The M.Sc./PGD in Knowledge Engineering is an advanced course intended for graduates who have either a computing degree or relevant qualifications and are interested in developing a professional understanding of the construction of knowledge based systems. The course has a modular structure and operates within a Postgraduate Credit Accumulation and Transfer Scheme. The course consists of two main elements: a taught element (which has a value of 70 CATS credits at level M) and a project, undertaken for an industrial/commercial or a research client (which has a value of 50 CATS credits at level M). Intermediate awards of Postgraduate Certificate and Postgraduate Diploma are available for students who wish to leave the course during or at the end of the taught part having gained 35 or 70 credits respectively. The Diploma is also available for award to those students who fail to deliver a satisfactory project. The major computing topics offered within the taught element of the course are :- STAGE 1 Expert Systems (5 credits) Knowledge Representation (5 credits) Knowledge Acquisition (5 credits) Knowledge Based Systems Design Methodologies (10 credits) Expert System Programming (10 credits) STAGE 2 Research Methods (5 credits) Adaptive Computation (10 credits) Natural Language Processing (5 credits) Architectures for Large Knowledge Based Systems (10 credits) Contempory Applications of Knowledge Engineering (5 credits) STAGES 1 and 2 Seminar Series STAGE 3 Project (50 credits) Delivery Modes ============== The course is for 1 year full time or 3 years part time ( 2 evenings per week). For further information and course syllabi contact :- Dr. S. L. Kendal Course Leader (M.Sc. Knowledge Engineering) School of Computing and Information Systems University of Sunderland Sunderland Tyne & Wear Tel. 00 44 091 5152756 email: simon.kendal@sunderland.ac.uk or see Web pages @ http://osiris.sunderland.ac.uk/ ------------------------------------------------------------------------------- This message | Submissions ai+ai-predoc@cs.cmu.edu was sent via | Subscribe/Unsubscribe ai+query@cs.cmu.edu the AI-PREDOC | Available mailing lists include mailing list. | AI-JOBS, LISP-JOBS, PROLOG-JOBS, AI-POSTDOC, AI-PREDOC