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Module

CEG2722 : Data Science 2

  • Offered for Year: 2020/21
  • Module Leader(s): Professor Philip James
  • Lecturer: Professor Stuart Edwards
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

This module introduces informatics in the context of spatial data manipulation and processing. It develops skills in the processing, analysis and manipulation of spatial data including vector, raster, image and position data. It builds on existing scripting skills and develops them in the spatial context. It provides an introduction to software and systems that will underpin further studies and facilitate individual research projects.

Outline Of Syllabus

This module covers:
•       Data in the spatial context
•       Vector and Raster models
•       Image manipulation
•       Using Data APIs and Time-Series processing
•       Processing GPS data
•       Linux command line and shell

Teaching Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials240:208:00Online lectures via recorded medium
Guided Independent StudyAssessment preparation and completion25:0010:00Assessment completion and report wrtiing
Scheduled Learning And Teaching ActivitiesLecture160:308:00Follow on exercise from lectures (1 per lecture)
Scheduled Learning And Teaching ActivitiesPractical31:003:00Lecture/practical PiP
Scheduled Learning And Teaching ActivitiesPractical81:008:00Synchronous practicals online
Guided Independent StudyDirected research and reading120:0020:00Directed readings from lectures
Guided Independent StudyIndependent study81:008:00Online exercises (follow on from Synchronous delivery)
Guided Independent StudyIndependent study130:0030:00Lecture follow up, background reading, reading beyond syllabus.
Scheduled Learning And Teaching ActivitiesModule talk11:001:00Synchronous Online
Guided Independent StudyOnline Discussion41:004:00Bi-weekly drop in Q and A
Total100:00
Teaching Rationale And Relationship

•       Students will be presented with new information and concepts through lectures.
•       Practicals will address key areas of the curriculum and develop specific skills in data handling and processing within the context of current software and tools
•       Lecture and practicals will demonstrate and utilise a range of software tools and libraries
•       Practicals in the Linux environment will develop Linux shell skills.
•       Assessment preparation will allow students to apply and practise their knowledge and skills to new problems

Alternatives will be offered to students unable to be present-in-person due to the prevailing C-19 circumstances.
Student’s should consult their individual timetable for up-to-date delivery information.

Assessment Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report1M60spatial data processing
Report1M40Linux data processing
Zero Weighted Pass/Fail Assessments
Description When Set Comment
ReportMScripting in Python (5hrs effort).
Assessment Rationale And Relationship

The assessment will:
•       demonstrate understanding of key spatial data structures through the access and manipulation of these data types and formats
•       assess the application of scripting within current software and tools
•       will require the mastery of a number of tools, libraries and environments for data manipulation and processing

Reading Lists

Timetable