Visualisation in Data Science (9781) |
| Credits: 3,0 | | Study load hours: 81 | Period: semester 2 (3sp)  |
| Language of instruction: English | | Exam contract: not possible |
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Mandatory sequentiality bound on the level of programme components
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Following programme components must have been included in your study programme in a previous education period
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Programming in Python (9772)
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3.0 stptn | |
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In data science, even the most powerful insights can fail to make an impact without clear communication. This course explores the art and science of data visualisation, guiding students through the principles of effective visual design to transform complex datasets into clear, compelling stories where intricate ideas become intuitive.
Content
- Fundamentals of data visualisation
- Overview of data visualisation techniques
- Principles and process of design
- Storytelling with data
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| Compulsory course material |
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All course material (course notes, handouts, video lectures and exercises) will be available on Blackboard. |
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Lecture ✔
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Project ✔
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Small group session ✔
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Semester 2 (3,00sp)
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| Written evaluation during teaching period | 100 % |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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Learning outcomes | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
Master of Statistics and Data Science
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- EC
| The student can work in a multidisciplinary, intercultural, and international team. | | | - DC
| The student is able to extract user tasks from domain experts. | - EC
| The student is able to correctly use the theory, either methodologically or in an application context or both, thus contributing to scientific research within the field of statistical science, data science, or within the field of application. | | | - DC
| The student is able to correctly use the theory methodologically, thus contributing to scientific research within the field of statistical and data science.
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| The student is capable of acquiring new knowledge. | - EC
| The student knows the relevant stakeholders and understands the need for assertive and empathic interaction with them. | | | - DC
| The student can identify relevant stakeholders and their interests, particularly within the programme specialization. |
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| Included in these programmes | Tolerance3 |
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Y
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.15.1, section 3. |
3 Education, Examination and Legal Position Regulations art.16.9, section 2.
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