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University of Gävle
Introduction to Machine Learning
In today's data-driven world, machine learning is revolutionizing industries from healthcare to finance to entertainment, and it is becoming increasingly essential to many fields. So, whether you are a student or a professional in the industry, machine learning skills are in demand. This course is a perfect starting…
- Higher education
- Information unavailable
- 31 August 2026
- Information unavailable
- Information unavailable
- 25 %
Overview
In today's data-driven world, machine learning is revolutionizing industries from healthcare to finance to entertainment, and it is becoming increasingly essential to many fields. So, whether you are a student or a professional in the industry, machine learning skills are in demand. This course is a perfect starting point to gain the skills needed to succeed in this exciting and rapidly growing field. Throughout the course, you will gain an in-depth understanding of supervised, unsupervised, and reinforcement learning methods and their practical considerations. You will be able to explain the ideas, assumptions, and intuition behind different machine-learning approaches and analyze relevant applications. The lectures, assignments, and project work are designed to provide you with hands-on experience in implementing machine learning methods in different applications. This course provides basic machine-learning skills to anyone interested in pursuing a career in data science, computer vision, or natural language processing but can be very useful in lots of other professions as well.
Admission scores
Entry requirements
Completed courses of at least 30 cr in Computer Science and Mathematics, including the courses Programming Methodology 7,5 cr and Linear Algebra 7,5 cr, or equivalent
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
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.hig.dvg337.18460.20262
- Last checked
- 2026-09-23T10:37:30.869721+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
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.hig.dvg337.18460.20262
- Offering identity in the source
- e.uoh.hig.dvg337.18460.20262
- Education-form source code
- HS
- Education code in the source
- DVG337
- Change time according to the source
- 2025-12-11T12:10:01
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.