Apologies for cross-postings.
The purpose of this message is to remind you about our distance
learning, postgraduate, continuing professional development programme
in Industrial Data Modelling (about to enter its fourth year) which
can lead to a variety of qualifications:
* Postgraduate Certificate
* Postgraduate Diploma
* MSc.
Don't let the title put you off - Industrial Data Modelling is merely
the application of statistical, mathematical and computing techniques
to industrial problems. The subject is closely related to
chemometrics, technometrics and biometrics.
This programme is aimed at science and engineering practitioners and
managers in industry, and looks at the modelling, analysis and
interpretation of data.
If you are interested in developing your own skills, or those of your
staff, our programme can help both you and your company. All companies
can benefit since they need to understand the messages hidden within
their data.
A multidisciplinary, practical approach ensures that the techniques
considered are at the forefront of those required by industry. Since
our programme has been developed in partnership with industry we are
confident that it tackles real, practical issues.
Delegates can start the programme at any time and study at their own
pace. Note that the enrolment date fixes the cost of all modules.
Applicants are normally required to have at least a second class
honours degree in science / engineering and to demonstrate an aptitude
for statistics and / or mathematics. Other qualifications will be
considered and professional experience will be taken into account.
The modules for the MSc (and from which those for the PGCert and PGDip
can be chosen) are shown below - each syllabus is detailed in the
programme brochure.
CORE
* Fundamentals of Mathematics and Statistics
* Model Fitting and Calibration
* Design and Analysis of Experiments
* Multivariate Analysis: Principal Components and Calibration
* Multivariate Analysis: Classification, Partial Least Squares and
Calibration
* Research Issues and Methodology
ELECTIVE (two from these four for the MSc)
* Quality and Process Control
* Communicating Statistics
* Data Smoothing and Forecasting
* Nonlinear Modelling
ADDITIONAL (for the MSc or, optionally, for the PGDip)
* Industrial Project
Involves an in-depth, industry-based project of interest to both the
delegate and his / her company.
There are no traditional examinations. Assessment for all modules is
via assignments and / or practical case studies / miniprojects.
Most delegates are sponsored by their companies, although flexible
methods of payment can be arranged for those who are not. The fee
(payable in stages) for MSc delegates enrolling before 31st July 1999
(there's still time to beat the deadline!) is 7680 pounds sterling
(820 pounds per module plus 1120 pounds for the project). For MSc
delegates enrolling between 1st August 1999 and 31st July 2000 the fee
will be 7950 pounds sterling (850 pounds per module plus 1150 pounds
for the project).
More information can be found on our Web site at
http://www.cms.dmu.ac.uk/Courses/MScIDM/
Further details, a copy of the recently updated programme flyer and
brochure and an application form may be obtained from myself. If using
Email it will be speedier if enquiries are addressed to indatmod
(rather than cj).
Feel free to pass this information to whoever you think might be
interested. If you know of other suitable Email addresses to which I
could send future messages about the programme please let me know.
All the best.
Colin.
========================================================================
Colin James
Programme Director - Industrial Data Modelling
Department of Medical Statistics
Faculty of Computing Sciences and Engineering
De Montfort University Phone ............ (+44) (0)116-250-6147
The Gateway Fax .............. (+44) (0)116-250-6114
Leicester LE1 9BH Email(Personal) ........... [log in to unmask]
UK Email(IDM) .......... [log in to unmask]
http://www.cms.dmu.ac.uk/Courses/MScIDM/
========================================================================
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|