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Practical Applications of Artificial Intelligence (SZF_212)

About Study Course

Department: Faculty of Social Sciences
ECTS:3
Course supervisor:Linda Alksne
Study type:Full time
Course level:Master's
Target audience:Management Science
Language:Latvian, English
Study course description Full description, Full time
Branch of science:Other social sciences

Objective

Familiarise students with the basic principles and applications of artificial intelligence (AI) and high performance computing (HPC), with a particular focus on computer vision and natural language processing (NLP).

Prerequisites

Students should have experience in Python programming, using libraries as NumPy, Pandas and TensorFlow/Pytorch. Be able to work with machine learning models, especially neural networks, and have an understanding of the basics of computer vision (CNN, image processing) and natural language processing (tokenization, Word embeddings, Transformer models).

Learning outcomes

Knowledge

1.Will be familiar with theoretical basics in computer vision and/or natural language processing (NLP)

Skills

1.Practical application of image and word processing techniques

Competence

1.Ability to develop and adapt computer vision and NLP solutions to specific needs

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