Data Visualisation
Duration
- One Semester or equivalent
Contact hours
- 108 Hours
On-campus unit delivery combines face-to-face and digital learning.
Aims and objectives
This unit prepares students to explore a range of techniques and technologies to develop narratives and visualisations of different types of data. These types of data could include open data sets, business, industrial or scientific. Students will undertake the process of collecting and cleansing the data, apply appropriate models and algorithms to achieve a set that is suitable for visualisation.
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Develop strategies to define the scope of the data presentation requirements.
2. Examine and report on the potential ethical and biases of interpreting data
3. Develop data models and apply machine learning to large data sets
4. Demonstrate high-level understanding of modelled data to produce insights
5. Produce data visualisations with the use of data-driven tools
6. Evaluate the output against the project scope and the organisations goals.
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Develop strategies to define the scope of the data presentation requirements.
2. Examine and report on the potential ethical and biases of interpreting data
3. Develop data models and apply machine learning to large data sets
4. Demonstrate high-level understanding of modelled data to produce insights
5. Produce data visualisations with the use of data-driven tools
6. Evaluate the output against the project scope and the organisations goals.
Unit information in detail
- Teaching methods, assessment, general skills outcomes and content.
Teaching methods
| Learning and Teaching Structure | ||
| Learning Activity | Duration/Location | Hours |
| Scheduled hours |
|
|
| Face to Face Contact | 12 weeks of classes (9 hours per week) Lab 1 5hrs x 12 weeks Lab 1 4hrs x 12 weeks | 108 |
| Unspecified Learning Activities (includes independent study, assignment preparation, revision) |
| 42 |
| TOTAL |
| 150 |
Assessment
| Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
| Project Portfolio (Report and research) | Individual | 30-40% | 3,4,5 |
| Case Study | Individual | 10-20% | 1,2 |
| Project Portfolio (Client Report & Presentation) | Group | 40-60% | 1,2,3,4,5,6 |
General skills outcomes
During this unit students will receive feedback on the following key generic skills:
• Teamwork Skills
• Problem Solving Skills
• Analysis Skills
• Communication Skills
• Ability to tackle unfamiliar problems
• Ability to work independently
• Teamwork Skills
• Problem Solving Skills
• Analysis Skills
• Communication Skills
• Ability to tackle unfamiliar problems
• Ability to work independently
Content
• Developing a narrative with data
• Ethics in collection and preparation of data
• Data Models
• Introduction into Machine Learning
• Data Visualisation tools
• Descriptive Statistics
• Ethics in collection and preparation of data
• Data Models
• Introduction into Machine Learning
• Data Visualisation tools
• Descriptive Statistics
Study resources
- References.
References
A list of reading materials and/or required texts will be made available in the Unit Outline.