Course - Master of Applied Statistics
Advanced Data Wrangling and Interactive Visualisation

Course - Master of Applied Statistics
Advanced Data Wrangling and Interactive Visualisation

Facts
Advanced Data Wrangling and Interactive Visualisation
Location
Aalborg
Tuition fees
- 15.000kr. (19.000kr. Non EU)
Duration
Spring 2026
ECTS
5
Application deadline
- 10th November 2025
Advanced Data Wrangling and Interactive Visualisation is a course from the 3rd semester of the Master in Applied Statistics.
During the course, you will gain advanced knowledge and hands-on skills within data science that will enable you to transform, analyse and visualise large, complex volumes of data into useful and value-generating visualisations for a range of purposes and stakeholders.
The course will provide you with knowledge and skills within:
- Database and SQL, including key concepts of relational databases, entity-relationship (ER) modelling and create-read-update-delete (CRUD) operations.
- Techniques to access and load data from external sources, including API, CSV, Excel and JSON, and the Extract Transform Load (ETL) process.
- Big data principles, including volume, variety and velocity.
- Methods for visualising high-dimensional data like, e.g., PCA, t-SNE, and/or UMAP.
- Techniques to create interactive visualisations to explore data and patterns in plots, e.g., faceted browsing, linked views and interactive dashboards.
- Retrievingand manipulating data with SQL: interpret and compose SQL statements to extract, filter and aggregate data stored in relational databases.
- Usage of libraries in Python to retrieve, transform and integrate data from external data sources.
- Design and implement interactive visualisations in Python using dedicated libraries, such as Plotly, Bokeh and Dash.
- Design and develop interactive dashboards using dedicated tools like Tableau or Dash.
Target Group and Outcome
Seminar Dates, Location and other Expenses
Admission Requirements and Further Information
Opportunities for single courses
Single courses is an opportunity for you who may not want to complete a full part-time programme.