FI1BBDV75 Data Visualisation
FI1BBDV75 Data Visualisation
- Course description
- Course codeFI1BBDV75
- Level of study5.1
- Program of studyData Analyst 2
- Credits7.5
- Course coordinatorBertram Haskins, Alec Du Plessis
This course introduces candidates to important visualization and graphing techniques which will enable their work to be represented using graphical illustrations. Data visualization is an important step to ensuring colleagues can interpret results at a glance without prior analytical knowledge. Candidates will be challenged to create intuitive graphs to represent their findings in a professional setting using relevant graphical generation and editing software. Additionally, candidates will make use of presentation software such as Microsoft PowerPoint to orally deliver their analysis to both a technical and non-technical business audience.
This course will provide candidates with the practical knowledge and skills to interpret and present the results of data analysis of any given datasets in visual contexts. Candidates will learn the universal design paradigm, thus providing them with the insights too create visually appealing, but also accessible graphics to ensure their findings are presentable to both technical and non-technical audiences.
The candidate:
- has knowledge of concepts, processes and tools that are used for creating data visualizations
- can update their own knowledge about data visualizations and apply the correct visualization to the corresponding problem domain at hand
- understands the importance of designs principles related to creating effective data visualizations
- has insights into user experience techniques to create accessible visualizations
The candidate:
- can apply knowledge of data visualization to select a subset of data for visualization
- can apply knowledge of communication techniques to allow a non-technical audience to understand the information being conveyed
- masters relevant tools and techniques to visualize data subsets
- masters slideshow software to create supporting presentation material
- can identify problem areas from a particular model and provide insights into appropriate solutions
The candidate:
- understands the ethical requirement for data visualizations on a data set
- has developed an ethical attitude in communicating data visualizations verbal presentations and publications
- can apply data visualization techniques based on the audience of the project
- can develop work methods to create visualization graphics for clients of data analysis projects
In this course, the following teaching and learning methods can be applied, but are not limited to:
- Lecture: Educator-led presentations or activities providing knowledge, skills, or general competencies in the subject area.
- Group work: Collaborative activities where students work together to solve problems or complete tasks.
- Tutoring: One-on-one or small group sessions with an instructor for personalized guidance and support.
- Student presentations: Opportunities for students to demonstrate their understanding of course material by presenting to peers.
- Online lessons: Digital content delivered via an online learning platform.
- Guidance: Individualized advice and direction from instructors to support students in their learning journey.
- Workshops: Practical sessions focused on hands-on application of theoretical concepts or skills.
- Self-study: Independent study where students engage with course material on their own without any teacher support.
Teaching materials, reading lists, and essential resources will be shared in the learning platform and software user manuals where applicable.
| Form of assessment | Grading scale | Grouping | Duration of assessment |
|---|---|---|---|
Course Assignment | Pass / Fail | Group/Individual | 1 Week(s) |