Agile Data Analysis for Sustainable Cities
3 courses on Data Science for Urban Mobility
Most European cities have a large amount of data related to public space availability and usage. With the spreading of new technologies, mainly thanks to the IoT (Internet of Things), more and more data will be available in the coming years.
However, to transform data into useful information it is fundamental to have people trained in Urban Mobility Data Science.
ADA, the Agile Data Analysis for sustainable cities and citizens activity of the EIT Urban Mobility, aims at reducing the knowledge gap existing in Big Data and Data Science among professionals and organizations of the urban mobility area through training courses, provided as Virtual Data Lab.
Moreover, the ADA course offers the possibility to have hands-on new anonymized Urban Mobility data using the European FIWARE platform.
COURSES
This course is devoted to describing the structure of a data-centric project and the tools to make the most of Big Data business objectives, creating a value chain. In particular, the course starts from the identification of city problems and analysis of requirements through a problem-driven approach.
Starting from the challenges and problems faced by European cities, drawing on the participants’ direct experience, the course teaches a methodology to go from the objectives to the implementation of actual data-driven strategies, including selection, acquisition, cleaning, and analysis of data.
This initial course teaches people how to use data centric approach to take decisions in the Urban Mobility field. Will teach non experts on data management people how the basics for Data analysis works, how machine learning and other artificial intelligence techniques works and how to use them in the field of Urban Mobility. We will learn how to use them, giving basic Python concepts, and we will guide them how to use them in a cloud based environment using the EDVL for their task. They will be able to get some results by themselves from a significant data set (fully guided).
The course is devoted to give an understanding on how you can understand the basic characteristics of your data and how a data-centric project can be planned by evaluating basic assumptions and answering initial domain questions.
The course presents methods to create an initial high level model which can be used as input/driver for advanced data science methods or "machine learning as a service" offerings. We also give an overview on how to evaluate the results of such methods and how to compare these results with the initial expectations to support domain validation.
WHO SHOULD ATTEND
Managers and decision-makers
Who wants to understand Data Science technology and applications in Urban Mobility
Who needs to identify and explore Data Science in Urban Mobility opportunities
Who wants to broaden their knowledge about the disruptive potential of Data Science in the Urban Mobility industry
Who wants to apply their expertise for the digital transformation of the cities
📅 Dates
December 13, 2021
December 16, 2021
Duration
5 hours in 2 days
Location
Synchronous online
€ Course fee
1.200€ FREE thanks to EIT Urban Mobility financing
🇬🇧 Language
English
📜 Certificate
A digital certificate of participation will be delivered upon completion of the programme
📍Registration
or
👩💼 Contact
Marco Brambilla (marco.brambilla@polimi.it)
📅 Dates
November 24, 2021
November 25, 2021
Duration
8 hours in 2 days
Location
Synchronous online
€ Course fee
1.200€ FREE thanks to EIT Urban Mobility financing
🇬🇧 Language
English
📜 Certificate
A digital certificate of participation will be delivered upon completion of the programme
📍Registration
👩💼 Contact
Joaquín Salvachúa (joaquin.salvachua@upm.es)
📅 Dates
December 14, 2021
Duration
1 day
Location
Synchronous online
€ Course fee
1.200€ FREE thanks to EIT Urban Mobility financing
🇬🇧 Language
English
📜 Certificate
A digital certificate of participation will be delivered upon completion of the programme
📍Registration
👩💼 Contact
László Gönczy (gonczy.laszlo@vik.bme.hu)
TESTIMONIALS
Cities today are facing a variety of challenges. The city of Milano, Italy has identified the following challenges for the urban plan for sustainable mobility: increasing accessibility of public spaces and mobility services, reducing dependency on private vehicles, redistributing public space in favour of active mobility, reducing road accidents, reducing the exposure to noise and air pollutants, enhancing freedom of choice to more sustainable modes of transport.
Today, the health emergency connected to COVID-19 has set us new challenges, such as the change in mobility behaviour of citizens and commuters due to the reduction in public transport capacity and the propensity to smart working.
Data has become extremely valuable for addressing all these challenges, especially from a business perspective. Improving data within an organization has the potential to deliver value in many areas. It can help lower costs and increase profits but also reduce risks. The data-driven approach allows companies to anticipate changes and challenges more effectively and accurately.
Interview with Andrea Canevazzi (AMAT Milan)
With ADA you can use your data for a better organization of your city
Juan Quemada (UPM Professor)
Turning data into decisions in an easy way
Joaquín Salvachúa (UPM Professor)
Discover how to get big insights from your big data.
This course will provide you with the theoretical and practical knowledge to make your organisation's data profitable.
Fabián García Pastor (Enlanza Senior Advisor for Innovation and Digital Transformation | UPM Professor)
Data driven approaches help business users to create solutions within a couple of days.
In our company, millions of lines of data is being created each day, therefore we need novel approaches and technologies.
Interview with Ferenc Mezőhegyi (Magyar Közút Zrt-Hungarian utility for maintaining and developing road infrastructure)