SHE level 10 SCQF credit points 20 ECTS credit points 10 Module code MHI225680 Module Leader Yan Zhang School School of Science & Engineering Subject Computing Trimester A (September start)
Summary of content This module will introduce the challenges and possible solutions around manipulating and analysing various datasets of different shapes and formats. The module is designed to help students learn to build and apply tools that are required to derive business value from data. The tools will range from data preprocessing, analysis to visualization tools.
Module details Syllabus arrow_forward Overview
Learning outcomes arrow_forward On completion of the module the student should be able to:
Teaching / learning strategy arrow_forward The university 'Strategy for Learning' documentation has informed the learning and teaching strategy for this module. The module's material will be introduced through lectures while practical programming and problem solving exercises, based on the lecture material, will be given to students for their laboratory sessions. All lecture and laboratory material will be made available on GCU Learn. A number of the technologies and approaches presented in the course have a large amount of external material online e.g. open source toolkits, data sources, video, tutorials etc. and links to these will be provided to the students. This also ensures that students have access to the most up to date technologies and tools being used in the area of big data. During all laboratory sessions students will receive formative feedback on their performance in undertaking the laboratory exercises. Summative feedback and grades will also be provided for the coursework assignment undertaken as part of the module using GCU Learn. GCU Learn will also be used to provide the students with module specific forums and wiki's to stimulate student and lecturer interaction out with the normal lecture and laboratory sessions.
Indicative reading arrow_forward Transferrable skills arrow_forward Specialist knowledge and application
Module structure Activity Total hours Lectures 24.00 Tutorials 0 Practicals 24.00 Seminars 0 Independent Learning 132.00 Assessment 20.00 Placement 0
Assessment methods Component Duration Weighting Threshold Description Course Work001 50 35 Class assessment: written paper/on-line test Course Work002 50 35 Problem based assessment
