Education

BSc in Data Science and Machine Learning

Department of Computer Science, Aalborg University · 2024–2027. Three years of programming, mathematics, statistics and machine learning, taught the Aalborg way: every semester, half the credits come from a project solved in a small group.

Official curriculumDownload CV
Draft. Course names are my English translations of the official module titles; one-line descriptions and project placeholders need your input.
Credits
180 ECTS over six semesters
Projects
One group project per semester, 5–20 ECTS each
Core
Programming, statistics, linear algebra, ML, databases
Specialism
Graphs, web intelligence and big-data systems

Semester by semester. The group project first, then the courses.

Semester1Autumn 2024
Group project · 5 ECTS

Basic data analysis with spreadsheets

P0: first group project, learning the problem-based way of working.

  • Programming for data analysis10 ECTSProject module (P1): a data-analysis program built in a group.
  • Introductory programming for data science5 ECTSPython fundamentals: control flow, functions, data structures.
  • Calculus5 ECTSLimits, derivatives, integrals and their use in modelling.
  • Problem-based learning5 ECTSAAU's PBL method: problem formulation, group work, project reports.
Semester2Spring 2025
Group project · 10 ECTS

From data to science

[Our group project: title, and one line on what we built and found.]

  • Applied statistics5 ECTSEstimation, hypothesis tests and regression in practice.
  • Linear algebra5 ECTSVectors, matrices, eigenvalues: the language of most ML methods.
  • Algorithms and data structures5 ECTSComplexity, sorting, graphs, dynamic programming.
  • Data visualisation5 ECTSDesigning figures and dashboards that tell the truth about data.
Semester3Autumn 2025
Group project · 15 ECTS

Data analysis via machine learning

[Our group project: title, and one line on what we built and found.]

  • Database systems5 ECTSRelational modelling, SQL, transactions and indexing.
  • Object-oriented programming fundamentals5 ECTSClasses, interfaces and design in an OO language.
  • Machine intelligence5 ECTSSearch, probabilistic reasoning, Bayesian networks and learning.
Semester4Spring 2026
Group project · 15 ECTS

[Statistical data analysis / Advanced data mining]

[Our group project: title, and one line on what we built and found.]

  • Big data systems5 ECTSDistributed storage and processing at scale.
  • Statistical learning5 ECTSLinear models, regularisation, resampling and model selection.
  • Data mining5 ECTSPattern mining, clustering and classification on large datasets.
Semester5Autumn 2026
Now
Group project · 15 ECTS

Analysis of graph-related data

Graph recommender systems. Our group compares popularity, classical and graph-based recommenders (LightGCN), supervised by Yu Zhang. [one line on the result or question]

  • Graph data analysis5 ECTSGraph models, random walks, sampling and graph learning.
  • Web intelligence5 ECTSInformation retrieval, recommender systems and web mining.
  • IT law5 ECTSData protection (GDPR), IT contracts and liability.
Semester6Spring 2027
Next
Group project · 20 ECTS

Bachelor project

[topic, once chosen]

  • Data security and privacy5 ECTSThreat models, cryptographic tools and privacy-preserving analysis.
  • Trends in machine intelligence5 ECTSCurrent research directions in AI and machine learning.