FM1AZDV05 Data Visualisation
FM1AZDV05 Data Visualisation
- Course description
- Course CodeFM1AZDV05
- Level of Study5.1
- Program of StudyApplied Machine Learning
- Credits5
- Study Plan CoordinatorLeon Grobbelaar
The course provides knowledge of the strengths and weaknesses of concepts and processes within big data visualisation. Candidates are provided with skills with tools and techniques for different data types. The course also provides practical skills in reviewing, selecting and the use of data visualisations techniques for datasets. Candidates are provided with an understanding of aspects of design principles and aesthetics.
This course will provide students with the practical knowledge and skills to interpret and present the results of the machine learning analysis of large datasets using suitable formats and mediums, in appropriate contexts, and to appropriate levels of granularity.
The candidate:
- has knowledge of concepts, processes and tools that are used for generating effective and situation-appropriate data visualisations
- can update his/her knowledge about data visualisations
- understands the importance of the design principles for creating and evaluating effective data visualisations
The candidate:
- can apply knowledge of data sets and data visualisation to select appropriate data for visualisation
- masters relevant tools and techniques to visualise data from datasets
- can study data sets and identify strengths and limitations and what measures need to be implemented
The candidate:
- can carry out a data visualisation of large data sets
- can develop and communicate data visualisations
Digital Learning Resources
The learning management system (LMS) is the primary learning platform where students access most of their course materials. The content is presented in various formats, such as text, images, models, videos or podcasts. Each course follows a progression plan, designed to lead students through weekly modules at their own pace. Exercises and assignments (individual or in groups) are embedded throughout the courses to support continuous practice and assessment of the learning outcomes.
Campus Resources
In addition to the digital learning resources, campus students participate in physical learning activities led by teachers as part of the overall delivery.
Guidance
Guidance and feedback from teachers support students' learning journeys, and may be provided synchronously or asynchronously, individually or in groups, via text, video or in-person feedback.
| Form of assessment | Grading scale | Grouping | Duration of assessment |
|---|---|---|---|
Course Assignment | Pass / Fail | Group/Individual | 3 Week(s) |