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Published education catalogue

Data Science & Machine Learning

Education information from the published source. The education record and its time-bound offerings are kept separate.

Education facts

Code: GIK2KM

The course covers the process of data science, i.e. a multidisciplinary approach to find, extract and discover patterns in data through a fusion of analytical methods, domain expertise and technology. In this context, the fields of data mining, forecasting, machine learning, predictive analytics, statistics and text analytics are covered. Within the framework of the iterative data science process, business understanding is treated with problem identification for the specification of key variables that are to function as model goals and identification of relevant data sources. It also includes the formulation of questions that define business goals and that can be quantified by computer science technicians. To control data quality, the acquisition of raw data, data processing (ETL), examination of data and modeling are included. To facilitate the development of model(s) and to find the model that best answers the initial questions, so called feature engineering is used, when raw data is extracted and distinctive features are created. Finally, the evaluation of modeling and analysis, presentation of results and commissioning are discussed.

Entry requirements

Object-Oriented Programming 7.5 Credits, First cycle or other course in Fundamentals of Programming Statistical Analysis 7.5 credits

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

Source and updates

Skolverket Susa-navet

Retrieved: .

Published: .

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Publication version: 8e217193-f5fa-4778-b085-a4521fd03e8d

Checksum: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c

Last changed according to the source: 2026-03-23T10:20:10