Data Science: How to become a data wizard

General description

With the rapid development of technologies to capture and transmit human, sensor and machine-generated data, the opportunities for data scientists are growing rapidly.

This course is for beginners in data science who are interested in understanding the main concepts, methods and tools behind big data analytics and its applications. The aim is to cover the entire data science pipeline and to provide an integrated view on databases, data mining, machine learning and data visualization. The program includes lectures and practice problems using real-world data and case studies.

Despite all of the irresistible academic activities we have planned, you will also have the opportunity to visit the beautiful city of Aveiro and the surrounding areas, such as Praia da Barra and its charming beachside. You can also enjoy yourself at great parties, get to know amazing people from every corner of Europe and have lots of fun. Combine all this and you get the recipe for the greatest 10 days of your summer! Are you ready to accept this challenge?

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Academic information

Fields of activity:

Applied Sciences , Computational Sciences , Computer Engineering , Computer Science/Automatic Control/Informatics , Control Engineering/Systems engineering , Electronic/Electrotechnical Engineering , Mathematics , Telecommunications/Electronics

Content and topics:

-Data engineering: data modeling and management; spatial data representation and mapping; - Data mining: exploratory data analysis and pre-processing; neural networks; deep neural networks; classifiers and performance measures; - Intelligent agents: what is an agent; agent types, architectures and applications; - Data and information visualization; - Tools and platforms for big data analytics.

Learning goals and objectives:

Participants in the course will be able to: - Understand the main concepts, requirements, components and issues on data science; - Design a simple database and understand the processes of data management, transformation and integration from multiple sources; - Understand how to make sense of data and how to use techniques for data classification, inference and reasoning; - Apply data mining and machine learning techniques to common problems.

Examination type:

Written mini-test (exam) and oral presentation.

ECTS credits issued:

None

Information for applicants

Selection criteria:

Based on the motivation letter, topic interest, answers to our questions and overall creativity.

Practical arrangements

All of the following are covered by the event fee:

Lodging:

University dorms.

Meals:

3 meals per day, at least one of them hot. Home cooked traditional portuguese food.

Transportation:

Transportation will be guaranteed through the University bus and vans or organiser's cars.