Data Mining
The course provides an in-depth exploration of data mining and analysis techniques critical for modern data science applications.
Beginning with an introduction to ensemble methods, the course moves into sophisticated classification techniques alongside approaches for evaluating these models.
Students gain hands-on experience with advanced techniques for dimensionality reduction and clustering and their respective evaluation. The curriculum also covers time series analysis and forecasting methods, equipping students with skills for temporal data challenges.
In addition, the course includes Explainable AI (XAI) and survival analysis, providing a well-rounded view of practical and theoretical data science tools.
By the end, students are prepared to understand, apply and critically assess advanced data science models, preparing them to navigate complex real-world datasets effectively.
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Course structure
Teaching format
The teaching consists of lectures and guided exercises.
The teaching takes place in English.
During the course, a number of programming assignments must be solved. Those assignments must be approved before Written exam 1 can be taken. Written exam 1 checks that the student has understood the assignments that have been done.
Assessment
The course is examined through written exams:
Written exam 1, 3.5 credits, grade G/U
Written exam 2, 4 credits, grades A-FExaminer
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Schedule
The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course. -
Course literature
Note that the course literature can be changed up to two months before the start of the course.
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Contact
Study counsellors - master
- Visiting address
Nod Buildning, Borgarfjordsgatan 12, Kista
- Office hours
Please contact us via email if you want to book a meeting. We are available on Campus in Kista and via Zoom.
- Phone hours
Thursday 12.30–2 pm
- Irregular office hours
No phone hours on Thursday 1 May.
