2018/19 Taught Postgraduate Module Catalogue

GEOG5990M Programming for Geographical Information Analysis: Core Skills

15 creditsClass Size: 40

Module manager: Andy Turner
Email: a.g.d.turner@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2018/19

Pre-requisite qualifications

None, however, this module needs to replace GEOG5540M Introduction to Programming and Customisation as the pre-requisite for GEOG5080M Web-based GIS.

This module is mutually exclusive with

GEOG5991M	Programming for Geographical Information Analysis (WUN): Cor
GEOG5995M	Programming for Social Science: Core Skills

Module replaces

GEOG5540M Introduction to Programming and Customisation

This module is not approved as an Elective

Module summary

This module gives a complete basic training in computer programming using the Python language. Python is a key programming language for data analysis. On completion of this module, you should have the following skills and knowledge: -Foundation level computer programming for Geographical Information analysts. -Know how to build computer analysis and modelling tools for geographical data. -An understanding of how important elements of computers, such as the Web and file storage work. -Insight into industrial programming practice and frameworks. The vast majority of Geographical Information specialists are good at using `out of the box' functionality of software, but may be less good at enhancing this functionality or developing software to do specific tasks that cannot easily be done with existing software. This module will take you to the next level - the level at which you are no longer just a software user, but a software developer capable of developing bespoke tools for geographical analyses Python is often the language of choice for both environmental and business consultancies and it is widely used in research. The module is suitable for those with no experience of programming, or those with experience of other programming languages. The module is an excellent foundation for dissertation projects or work placement modules, and provides training suitable for the module GEOG5080M: Web-Based GIS. The module leads on to Programming for Geographical Information Analysis: Advanced Skills, which provides still higher-level training in GIS adaption and computer modelling. Students with pre-existing programming skills may like to look at the advanced module directly, but please discuss pre-requisites with the module convener.

Objectives

On completion of this module, students should:
Be able to develop Python programs for geographical data processing.
Be aware of the history of computer programming and the importance of software licensing and source code documentation.
Have developed an understanding of industry standards in software engineering.

Learning outcomes
Foundation level computer programming for geographical data processing.
Awareness of the breadth and depth and development of the Python language.
An understanding of how important elements of computers, such as the Web and file storage work.
Insight into industrial programming practice and frameworks.

Syllabus

-Python architecture / history
-The core language: variables, arrays, flow controls
-Functions
-Classes/Objects

-Documentation

-Input/output
-Useful libraries

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	11	2.00	22.00
Practical	11	2.00	22.00
Private study hours			106.00
Total Contact hours			44.00
Total hours (100hr per 10 credits)			150.00

Private study

Students are expected to engage with virtual learning resources to learn about Python and general programming in their private study time. Students will be given structured practical exercises and will also be expected to work on these independently between formal
practical support sessions. The students
will be supported through this work via the VLE and with online materials, and by formative assessment tasks

Opportunities for Formative Feedback

Student progress will be monitored through formative practical tasks. The assessment will be individual to each student; students will have the option of designing their own project (within some key limitations - for example, that the software must load and write data, and involve data analysis). Students will have access to assessment-orientated materials, including walk-through discussions of structuring solutions and the coding that might be involved.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Computer Exercise	Independent project (2,500 words equivalent)	70.00
Portfolio	Portfolio of practical work (1,500 word equivalent)	30.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 17/09/2018

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