IT, data og digitalisering

Introduction to Image Analysis and Machine Learning - Bachelor


The course assumes the student has the ability to program in some imperative programming language (Java, Python, C/C++/C#. This is normally obtained by following the first semester undergraduate course Grundlæggende Programmering (GPP) however some additional programming experience is beneficial.

The course uses concepts from mathematics and in particular linear algebra. Fulfilling the general admittance requirements for BSWU ensures the mathematical prerequisites.

After the course, the student should be able to:

- Define, describe and relate concepts and mechanisms underpinning computer vision (CV) and machine learning (ML) methods and how they are related.

- Analyze and explain key aspects of building medium-sized computer vision applications.

- Explain, design and implement medium-sized interactive computer vision applications using concepts from ML.

- Evaluate, select and adapt appropriate computer vision and machine learning techniques by applying the theoretical concepts and practical techniques from the course.

- Clearly explain and employ basic linear algebra for computer vision and machine learning.

- Apply the theory and implement rudimentary research papers within CV and ML as expected on a bachelor level

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Det praktiske

  • Kursusudbyder: IT-Universitetet
  • ECTS-point: 7,5
  • Undervisningssprog: Engelsk
  • Udbudt til: Forår
  • Tilmeldingsfrist: 10. januar 2019
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