Neural Networks

Education facts

Code: FIM720

<p>The course gives an overview and a fundamental theoretical understanding of the most important neural net algorithms. These include models of associative memory algorithms for learning from examples (e.g., perceptron learning, back-propagation, temporal difference learning), and models for self-organization. Through comparison with methods from statistics and computer science students can develop an understanding of when neural networks are useful in application problems.</p>

Entry requirements

A Bachelor's degree in Engineering, Natural or Mathematical sciences of 180 credits including knowledge of Mathematical analysis, Linear algebra and Programming. Applicants must prove their knowledge of English: English 6/English B from Swedish Upper Secondary School or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

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.

• Neural Networks

  University of Gothenburg

  Start date: 2 September 2024

  End date: 3 November 2024

  Pace of study: 50 %