All-provider course timetable
Friday 22 October 2010
| 09:30 |
This is an introduction to the popular database package Microsoft Access 2007. The course is aimed at those who have never used the package before or have just started using it. There is an Access Fast Track course that is a shortened version of this course for those who learn at a faster pace. |
| 14:00 |
LECTURING AND PERFORMANCE 4
Finished
test course description |
| 14:15 |
Matlab: Basics
Finished
Matlab is a software package for numerical computation with high quality graphics facilities. This course is for beginners and new users of the package and describes basic concepts and use of Matlab, but not any other optional 'Toolboxes' available from the developers of MATLAB. |
Sunday 24 October 2010
| 09:00 |
Lecturing
Finished
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Monday 25 October 2010
| 09:00 |
Lecturing
Finished
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| 09:30 |
Microsoft Excel is the chosen spreadsheet package as it is a popular choice, both on Macintosh and PC. |
| 14:00 |
Module 6: Spatial Data Analysis
Finished
Introducing students to methods of data analysis that are relevant to spatial data. Discussing nature of Geographic Information Science (GISc), describing how space is conceptualised and represented in a GIS. |
| 14:15 |
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. |
| 16:00 |
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. This foundational course is for eligible graduate students who have no prior training in statistics. It introduces students to the basic general concepts that underlie descriptive and inferential statistics. It is divided into 4 sessions:
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Tuesday 26 October 2010
| 09:30 |
The Cisco Certified Network Associate (CCNA) programme is open to University IT Supporters. It covers network technology, protocols and theory at deeper levels reflective of university practices. There is a fee to attend this course. You will learn the basics of routing, switching, and advanced technologies to acquire the skills required to provide a robust and secure network in your institution's and it prepares you for CCNA certification. We offer this program as instructor led with remote access to the curriculum and an online networks laboratory called NETLAB. There is a mix of lecture, demonstrations and a heavy emphasis on practical activities using live lab equipment and a simulation package. Further details and pricing information are available. This is the second module of four modules in the CCNA programme. 1. Networking Fundamentals 2. LAN Switching and Wireless 3. Routing Protocols and Concepts 4. Accessing the WAN |
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Stata is a powerful general purpose statistical package. This course is for beginners and fairly new users of the package. Basic concepts and use of Stata will be introduced. The main aim of the course is to give participants a foundation and some background. However statistical techniques are not covered (see note below). The first session looks at an overview of the Stata system and getting data into Stata format and the second looks at reporting, graphing and analyses. It is strongly recommended for anyone likely to use Stata for any but the very simplest analysis of the very simplest data. |
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| 10:30 |
This self-paced hands-on course gives a "quick start" introduction to Microsoft PowerPoint 2007 which is widely used software for preparing presentations. Participants work at their own pace using a workbook containing notes and exercises, with a demonstrator on hand to help. |
| 14:00 |
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. This foundational course is for eligible graduate students who have no prior training in statistics. It introduces students to the basic general concepts that underlie descriptive and inferential statistics. It is divided into 4 sessions:
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This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences. This foundational course is for eligible graduate students who have no prior training in statistics. It introduces students to the basic general concepts that underlie descriptive and inferential statistics. It is divided into 4 sessions:
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| 14:15 |
R: Regression Analysis in R
Finished
This course is for new users who have learnt how to get data into R already, and know how to operate basic syntax. Emphasis will be on examples of running applied analyses of regression models for continuous, binary and ordinal outcomes using standard R procedures. Half a dozen libraries will be introduced that enables importing of data and running of linear, binary, ordinal and nominal outcome regression models in R. |
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Google is unarguably the world's most used search engine - but how good is it for academic research? This session aims to demonstrate how to make best use of Google and Google scholar for research purposes, whilst outlining some of the pitfalls of over-relying on them! |
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| 16:00 |
Module 5: Further Regression Topics
Finished
This module is concerned with greater knowledge of regression, through extension of the simple linear model; enabling students to assess the models they use, testing for problems such as collinearity, outliers/leverage, and heteroskdasticity. |
Wednesday 27 October 2010
| 09:30 |
R: Regression Analysis in R
Finished
This course is for new users who have learnt how to get data into R already, and know how to operate basic syntax. Emphasis will be on examples of running applied analyses of regression models for continuous, binary and ordinal outcomes using standard R procedures. Half a dozen libraries will be introduced that enables importing of data and running of linear, binary, ordinal and nominal outcome regression models in R. |
|
Stata is a powerful general purpose statistical package. This course is for beginners and fairly new users of the package. Basic concepts and use of Stata will be introduced. The main aim of the course is to give participants a foundation and some background. However statistical techniques are not covered (see note below). The first session looks at an overview of the Stata system and getting data into Stata format and the second looks at reporting, graphing and analyses. It is strongly recommended for anyone likely to use Stata for any but the very simplest analysis of the very simplest data. |
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| 11:30 |
How To Do A Literature Search
Finished
Are you about to embark on a dissertation, thesis, or piece of extended research? Before you can contribute to the academic dialogue, you need to have a sound grasp of your topic and its context. This session will give you strategies for finding and evaluating published literature so you can get a 'big picture' view of your topic. |
| 12:00 |
Time Management FOR TESTING
Finished
Would you like to be in control of your day, enhance your reputation and gain more job satisfaction? Then this is the course for you! You will learn many practical time management tips to help you work smarter, not harder. This course will cover setting priorities, dealing with interruptions, managing the paper mountain and email avalanche, guidelines for saying ‘no’ and it will show you how to change your use of time. |
| 14:00 |
This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research |
| 14:15 |
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. |
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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. |
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Mathematica: Basics
Finished
This course is part of the Scientific Computing series. Mathematica is a software package for numerical computation, symbolic manipulation and the production of graphics from mathematical functions and data. This course is for beginners and new users of the package and describes basic concepts and use of Mathematica. |
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| 16:00 |
Orientation tour
Finished
The UL is unique: a national, legal deposit library with an amazing collection of around 8 million items - over two million of which you can browse on our open shelves. If that sounds a bit daunting, why not come on a brief orientation tour to help you find your way around? We’ll even tell you what we keep in the famous Library tower ... |