Data Mining is an advanced Smarter course from Örebro University about uncovering useful patterns and insights in large datasets. You move from exploratory data analysis - preprocessing, visualisation and statistical techniques - to pattern-recognition methods such as association rule mining, anomaly detection and clustering. The course helps you support data-driven decision-making and prepare data well before building advanced AI models. It is given in English at distance with a few mandatory meetings on campus.
Duration: 3 months
Format: Hybrid
Location: Örebro
Language: English
Level: Advanced
Time commitment: approx. 80 hours over one semester, part-time; distance learning with mandatory meetings
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About the course.
This certifies that the participant has gained knowledge of data mining techniques for uncovering patterns and insights in large datasets. The participant can apply these methods to support data-driven decision-making and prepare data for advanced AI models.
This certifies that the participant has gained knowledge of data mining techniques for uncovering patterns and insights in large datasets. The participant can apply these methods to support data-driven decision-making and prepare data for advanced AI models.
What you will learn
What you learn.
You can apply methods for exploratory data analysis, including preprocessing and visualisation.
You can use statistical techniques to understand large datasets.
You can apply pattern recognition such as association rules, anomaly detection and clustering.
You can discover new and useful information in large datasets.
You can prepare and quality-assure data for further AI modelling.
Curriculum
How the course is built.
Exploratory data analysis
Preprocessing, visualisation and statistical techniques for understanding data.
Association rules
Finding relationships and rules in large datasets.
Anomaly detection
Identifying deviations and unusual patterns in data.
Clustering
Grouping data and discovering structure without labelled answers.
From data to AI
Preparing and quality-assuring data for advanced AI modelling.
Target audience
Who is this for?
For professionals who work with data and want to be able to find patterns and insights in large datasets as a basis for data-driven decisions and AI. Prerequisites: 180 credits including 15 credits of programming, and English 5/English A.
What "verified" means here
Verified credential.
When you complete the course, Örebro universitet issues your certificate. Your name, the course content and the issue date are encrypted and secured on blockchain, so it cannot be changed, and anyone can check that it is genuine.
100% Verifiable certificates Secured on blockchain
