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micro-module

Machine Learning

Machine Learning

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DescriptionOutcomesPotential progressInformationProviders

Description

The micro course intends to contribute to the current need for digitalization of the industry (Industry 4.0). It will contribute to the preparation of high level experts (engineers) able to deal with advanced technologies, including applications of artificial intelligence. Learn data science underlying concepts and learn the most frequently used techniques for information and knowledge extraction from big data.

The Team

PG
Profile photo
Pétia Georgieva
Teacher
6 learners
Study format
Online
Application period
1 June – 30 June 2023
Study period
1 November – 20 December 2023
Credits
3 ECTS
Pace
50%
Hosting university
University of Aveiro
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Learning outcomes

Fundamentals of machine learning

Learn the fundamentals of machine learning – regression, classification, clustering, short introduction to deep learning.

ESCO SKILLS

English

Build and optimize (linear, non-linear) data representation models.

Build and optimize (linear, non-linear) data representation models. Model performance and comparison.

ESCO SKILLS

Use IT tools

Implement machine learning algorithms

Learn to implement machine learning algorithms in software programs (Python).

ESCO SKILLS

Computer programming

Apply machine learning algorithms

Apply machine learning algorithms in practical problems with varying nature.

ESCO SKILLS

Work in teams

Define the problems in machine learning

Define the problems in machine learning terminology and framework and choose the most relevant approach.

ESCO SKILLS

Think analytically

Potential progress

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Goal based on on your motivation scan

Language learning

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Entrepreneurship, technology and innovation

Inter-personal skills

Critical and innovative thinking

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Information

This Micro Module will give you tools and techniques in the field of digitalization of the industry (Industry 4.0), dealing especially with artificial intelligence. Learn data science underlying concepts, learn the most frequently used techniques for information and knowledge extraction from big data.  The course includes 18 contact hours and 81 working hours.

Our methodology is focused into “learning by doing” in which lab work will involve solving problems with some level of complexity, such as handwritten digit recognition, emotion recognition from images, image compression, etc. Learners will work in teams and will be guided by an instructor. The implementation programming language is Python (expecting that the students have learned it before). The lab work is strengthened by a rich variety of projects: medical data such as skin cancer detection from dermoscopic images; web data, financial and marketing applications, etc. The students are encouraged to propose project topics, validated by the instructor.

Hosting university

University of Aveiro

University of Aveiro