6 ECTS credits
150 h study time
Offer 1 with catalog number 4020567FNR for all students in the 2nd semester at a (F) Master - specialised level.
In this course, we study scalable algorithms to analyze big datasets. We aim to give students a broad overview of the big data ecosystem, yet also make it concrete so that the students understand the algorithms on a fundamental level. Additionally, we will guide the students in applying such algorithms to real-world problems.
We will cover the following aspects:
Expected background knowledge: For this course, we expect the students to have a decent knowledge of basic machine learning algorithms (e.g., Machine learning course) and a decent background on statistics, calculus and linear algebra.
Study material: Scientific papers, course slides, book “Mining of Massive Datasets” (freely available at mmds.org) and Canvas notes.
The final grade is composed based on the following categories:
Written Exam determines 50% of the final mark.
Practical Exam determines 50% of the final mark.
Within the Written Exam category, the following assignments need to be completed:
Within the Practical Exam category, the following assignments need to be completed:
Written exam: 50% of the final grade.
Personal project: 50% of the final grade.
To be eligible to take part in the written exam, the student is expected to register for the project.
This offer is part of the following study plans:
Master in Applied Sciences and Engineering: Computer Science: Artificial Intelligence (only offered in Dutch)
Master in Applied Sciences and Engineering: Computer Science: Multimedia (only offered in Dutch)
Master in Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering (only offered in Dutch)
Master in Applied Sciences and Engineering: Computer Science: Data Management and Analytics (only offered in Dutch)
Master of Applied Sciences and Engineering: Computer Science: Artificial Intelligence
Master of Applied Sciences and Engineering: Computer Science: Multimedia
Master of Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering
Master of Applied Sciences and Engineering: Computer Science: Data Management and Analytics