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All-provider course timetable

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Fri 30 Oct 2020 – Mon 16 Nov 2020

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Friday 30 October 2020

10:00
Course to test optional sessions and the wait list new (3 of 3) Finished 10:00 - 11:00 Test Provider Lecture Room

« Description not available »

Course to test optional sessions and the wait list new (3 of 3) Finished 10:00 - 11:00 Test Provider Lecture Room

« Description not available »

14:15
Programming Concepts: Introduction for Absolute Beginners (1 of 2) Finished 14:15 - 17:00 UIS Online Microsoft Teams 1

This course is part of the Scientific Computing series.

This course is aimed at those new to programming, or who have never been formally taught the principles and basic concepts of programming. It provides an introduction to the basic concepts common to most high level languages (including Python, Java, Fortran, C, C++, Visual Basic). The aim of the course is to equip attendees with the background knowledge and confidence necessary to tackle many on-line and printed programming tutorials. It may also help attendees in deciding which programming language is suitable for their programming task.

Knowledge of the concepts presented in this course is a pre-requisite for many of the other courses in the Scientific Computing series of courses (although not for the "Python for Absolute Beginners" course).

17:00
Test course for bookings new Finished 17:00 - 18:00 Test Provider Lecture Room

« Description not available »

Saturday 31 October 2020

14:15
Programming Concepts: Introduction for Absolute Beginners (2 of 2) Finished 14:15 - 17:00 UIS Online Microsoft Teams 1

This course is part of the Scientific Computing series.

This course is aimed at those new to programming, or who have never been formally taught the principles and basic concepts of programming. It provides an introduction to the basic concepts common to most high level languages (including Python, Java, Fortran, C, C++, Visual Basic). The aim of the course is to equip attendees with the background knowledge and confidence necessary to tackle many on-line and printed programming tutorials. It may also help attendees in deciding which programming language is suitable for their programming task.

Knowledge of the concepts presented in this course is a pre-requisite for many of the other courses in the Scientific Computing series of courses (although not for the "Python for Absolute Beginners" course).

Sunday 1 November 2020

14:00
Module 6: Spatial Data Analysis (4 of 8) Finished 14:00 - 16:00 Geography Dept

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.

16:00
Module 1: Foundations in Statistics (Series 1) (4 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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:

  • Session 1: Variables and Measurement
  • Session 2: Describing a Variable
  • Session 3: Populations and Samples
  • Session 4: Statistical Models and Significance Tests

Monday 2 November 2020

14:00
Module 1: Foundations in Statistics (Series 3) (4 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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:

  • Session 1: Variables and Measurement
  • Session 2: Describing a Variable
  • Session 3: Populations and Samples
  • Session 4: Statistical Models and Significance Tests
Module 1: Foundations in Statistics (Series 2) (4 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

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:

  • Session 1: Variables and Measurement
  • Session 2: Describing a Variable
  • Session 3: Populations and Samples
  • Session 4: Statistical Models and Significance Tests
16:00
Module 5: Further Regression Topics (4 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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.

Tuesday 3 November 2020

10:00
Module 18: Researching Organisations (1 of 3) Finished 10:00 - 12:00 8 Mill Lane Lecture Room 4

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

14:00
Module 16: Comparative Historical Methods (4 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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

Sunday 8 November 2020

14:00
Module 6: Spatial Data Analysis (5 of 8) Finished 14:00 - 16:00 Geography Dept

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.

16:00
Module 2: SPSS and Descriptive Statistics (Series 1) (1 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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 module is essential for the statistical methods modules, which follow.

Monday 9 November 2020

14:00
Module 12: Designing Surveys (1 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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 module aims to provide students with an overview of survey methods, uses and limitations; to introduce students to the practicalities of design and use of surveys; to examine complexities of question and answer process; to examine practicalities of survey sampling and response.

Module 2: SPSS and Descriptive Statistics for Judge Students (1 of 4) Finished 14:00 - 17:00 Judge Business School, Computer Room

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 module is essential for the statistical methods modules.

Module 2: SPSS and Descriptive Statistics (Series 2) (1 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

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 module is essential for the statistical methods modules, which follow.

Module 2: SPSS and Descriptive Statistics (Series 3) (1 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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 module is essential for the statistical methods modules, which follow.

16:00
Module 7: Regression and binary and categorical outcomes (1 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

Module is designed to teach students how to analyse different types of data using SPSS; including outputs, conducting diagnostic tests, calculating effect sizes and make predictions.

Tuesday 10 November 2020

10:00
Module 18: Researching Organisations (2 of 3) Finished 10:00 - 12:00 8 Mill Lane Lecture Room 4

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

14:00
Module 17 Conversation and Discourse Analaysis (1 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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

Sunday 15 November 2020

09:30
Cisco CCNA for IT Supporters: Module 2 - LAN Switching and Wireless new charged (1 of 11) Finished 09:30 - 13:00 Balfour Macintosh Room

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

14:00
Module 6: Spatial Data Analysis (6 of 8) Finished 14:00 - 16:00 Geography Dept

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.

16:00
Module 2: SPSS and Descriptive Statistics (Series 1) (2 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

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 module is essential for the statistical methods modules, which follow.

Monday 16 November 2020

14:00
Module 12: Designing Surveys (2 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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 module aims to provide students with an overview of survey methods, uses and limitations; to introduce students to the practicalities of design and use of surveys; to examine complexities of question and answer process; to examine practicalities of survey sampling and response.

Module 2: SPSS and Descriptive Statistics for Judge Students (2 of 4) Finished 14:00 - 17:00 Judge Business School, Computer Room

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 module is essential for the statistical methods modules.

Module 2: SPSS and Descriptive Statistics (Series 2) (2 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

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 module is essential for the statistical methods modules, which follow.

Module 2: SPSS and Descriptive Statistics (Series 3) (2 of 4) Finished 14:00 - 16:00 Titan Teaching Room 2

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 module is essential for the statistical methods modules, which follow.

16:00
Module 7: Regression and binary and categorical outcomes (2 of 4) Finished 16:00 - 18:00 Titan Teaching Room 2

Module is designed to teach students how to analyse different types of data using SPSS; including outputs, conducting diagnostic tests, calculating effect sizes and make predictions.

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