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Mälardalen University

Predictive Data Analytics

The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling About this course The course aims to give insights in fundamental co…

  • Higher education
  • Information unavailable
  • 15 September 2025
  • Information unavailable
  • Information unavailable
  • 25 %

Overview

The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling About this course The course aims to give insights in fundamental concepts of machine learning for predictive analytics to provide actionable, i.e., better and more informed decisions in, forecasting. It covers the key concepts to extract useful information and knowledge from data sets to construct predictive modeling. Introduction: overview of Predictive data analytics and Machine learning for predictive analytics. Data exploration and visualization: presents case studies from industrial application domains and discusses key technical issues related to how we can gain insights enabling to see trends and patterns in industrial data. Predictive modeling: consists of issues in construction of predictive modeling, i.e., model data and determine Machine learning algorithms for predicative analytics and techniques for model evaluation. You will learn * Select suitable machine learning algorithms to solve a given problem for predictive data analytics. * Explore data and produce datasets suitable for analytical modeling. * Basics of machine learning for predictive analytics

Admission scores

Uppgift saknasVerified data is not connected to this education offering.

Entry requirements

90 credits of which at least 60 credits in Computer Science or equivalent, including 15 credits in programming as well as 2,5 credits in basic probability theory and 2,5 credits in linear algebra, or equivalent.  In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.

Source, measure and data quality
Source
Skolverket Susa-navet
Period
2025-09-15
Measure
Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
Population
Education offering e.uoh.mdu.dva478.24577.20252
Last checked
2026-09-23T10:38:46.21657+00:00
Limitation
Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.

Programme content

Uppgift saknasVerified data is not connected to this education offering.

Study structure

Uppgift saknasVerified data is not connected to this education offering.

Application and important dates

  1. Programme or course starts
  2. Programme or course ends

Salary and salary distribution

Uppgift saknasVerified data is not connected to this education offering.

Common occupations after graduation

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Students

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Geographical background

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Previous upper-secondary schools and programmes

Uppgift saknasVerified data is not connected to this education offering.

Completion and outcomes

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About the provider

Mälardalen University

Provider for the published education offering.

Sources and data quality

Education facts for the selected offering come from Skolverket Susa-navet.

Retrieved . Published . Times are shown in Swedish local time.

Source identity and publication version
Publication version
8e217193-f5fa-4778-b085-a4521fd03e8d
Education identity in the source
i.uoh.mdu.dva478.24577.20252
Offering identity in the source
e.uoh.mdu.dva478.24577.20252
Education-form source code
HS
Education code in the source
DVA478
Change time according to the source
2025-03-14T10:56:36

The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.