All-provider course timetable

This course is part of the Scientific Computing series.

This course is aimed at those new to programming and provides an introduction to programming using Python, focussing on scientific programming. This course is probably unsuitable for those with significant programming experience. By the end of this course, attendees should be able to write simple Python programs and to understand more complex Python programs written by others.

As this course is part of the Scientific Computing series, the examples chosen are of most relevance to scientific programming.

Mplus (www.statmodel.com) is a syntax based commercial statistical software package for estimating models containing latent,or unobserved, variables. It has grown out of the tradition in statistical modelling known as SEM - Structural Equation Models, sometimes called LISREL models (this stands for linear structural relations modelling). However Mplus is much more comprehensive that this and can handle models for multivariate analysis with both continuous and categorical observed and latent variables e.g. probit and logistic regression models and their SEM equivalents. It also has capabilities for estimating latent classification and trajectory models, multilevel models, conducting Monte Carlo simulations, combining multiply imputed data sets, and handling complex data from survey samples. This course is intended to introduce new users to the basic code required to run half a dozen simple examples.

This course is intended for those already using Microsoft Access 2007 to store and retrieve data who wish to explore queries, forms and reporting. Those who have attended the Access Intro course will find this follows on seamlessly from where that course ended.

This course is intended for those already using Microsoft Access 2007 to store and retrieve data who wish to explore queries, forms and reporting. Those who have attended the Access Intro course will find this follows on seamlessly from where that course ended.

This course is part of the Scientific Computing series.

This full-day course introduces the Python programming language to programmers who are already familiar with another high level programing language such as C/C++, Fortran, Java, Perl or Visual Basic. The aim of this course is to give such programmers sufficient familiarity with Python that they can attend any of the more advanced Python courses organised by the Computing service and easily follow any of the widely available Python tutorials on the more complex aspects of the language.

This course covers all the material contained in the "Programming: Python for Absolute Beginners" course, but in a more abbreviated fashion suitable for those who already have significant programming experience. This course does NOT cover the more complex aspects of the language (for such topics see the other Computing Service Python courses), nor is there much explicit discussion of the object oriented features of Python.

This course is for new users who have learnt how to get data into Stata, and know how to operate basic syntax having completed the Basics course or through self-study with the student version or manuals. Emphasis will be on examples of running applied analyses of regression models for continuous, binary and ordinal outcomes using standard Stata procedures. Guidance will also be provided on further addons that may be of interest.

This course is for new users who have learnt how to get data into Stata, and know how to operate basic syntax having completed the Basics course or through self-study with the student version or manuals. Emphasis will be on examples of running applied analyses of regression models for continuous, binary and ordinal outcomes using standard Stata procedures. Guidance will also be provided on further addons that may be of interest.

This course is part of the Scientific Computing series.

This course will introduce more advanced aspects of the Python language than the "Python for Absolute Beginners" course or "Python for Programmers" courses. The course will cover topics such as file I/O in more detail than either of those two courses. Whilst the course will not cover the use of Python to produce graphical output, some mention will be made of how Python can be used to interface with tools such as gnuplot to produce graphical output of scientific data.

This course does not explicitly cover the object oriented aspects of the Python language.

This course is part of the Scientific Computing series.

This course will introduce more advanced aspects of the Python language than the "Python for Absolute Beginners" course or "Python for Programmers" courses. The course will cover topics such as file I/O in more detail than either of those two courses. Whilst the course will not cover the use of Python to produce graphical output, some mention will be made of how Python can be used to interface with tools such as gnuplot to produce graphical output of scientific data.

This course does not explicitly cover the object oriented aspects of the Python language.

An introduction to the bibliography package EndNote and its interface with Microsoft Word. EndNote is a program that stores bibliographic references, and notes about those references, in an EndNote Library. EndNote then interfaces with MS Word to help you create a bibliography and bibliographic citations while you type a document. The style (contents and layout) of the citations and bibliography can then be formatted in an Output Style of your choice; this can easily be changed without retyping.

This course is part of the Scientific Computing series.

This course will introduce methods in Python for accessing the operating system environment (e.g. standard input, standard output, environment variables, etc). The course will cover topics such as command-line parsing in more detail than the "Python Introduction for Absolute Beginners" or "Python Introduction for Programmers".

Following on from the "Photoshop: Basic Techniques" course, this course covers some of the more advanced feature of Adobe Photoshop, the popular image manipulation and editing tool for graphics and design professionals. The course will explore some of the more advanced features of Photoshop. Techniques will be explained and demonstrated, and participants will then be given the opportunity to practice these for themselves.

This course will introduce the use of PowerPoint in the production of presentation for use with slides, foils and direct projection.

This course is part of the Scientific Computing series.

This course explains how to construct and use regular expressions in Python (using the re module). It does not discuss how to construct complex regular expressions, nor does it cover regular expressions themselves in much detail, rather it focuses on how to use regular expressions in Python.

For a detailed discussion of regular expressions see the "Pattern Matching Using Regular Expressions" course.

This workshop will cover some of the more advanced features of PowerPoint with plenty of opportunity to ask questions. The workshop is largely driven by audience questions.

This course is part of the Scientific Computing series.

This course will cover the important programming tasks that used to be messy or complicated in Fortran 77, and can be done more cleanly and effectively in modern Fortran (i.e. Fortran 90/95/2003). It is intended for people who have been using Fortran for many years, but have not been following the recent standards. It is also intended for people who have an older, but still valid, Fortran program and want to clean it up and make it easier to understand and maintain. It will cover only aspects of old Fortran (i.e. Fortran 77) that can be improved by replacing them, and not the totally new aspects.