Smart City Foundations

About the course The e-learning course “Smart City and Data Management Foundations” is for people who want to use technology to solve real urban problems, whether you dream of starting a startup, growing in public administration, or planning a career in data and IT. You’ll learn what smart cities are, how urban data is collected and managed, and which technologies drive modern cities. Step by step, you’ll also see how smart solutions are designed and implemented in practice.

Who is this course for?

• Future Smart City specialists and Chief Data Officers.
• Employees of municipal offices and public institutions.
• Data analysts and data management professionals.
• Students of data analytics, transport, IT management, data engineering and related fields.
• Startup founders searching for ideas and niches in smart city solutions.

Why join this course?

• You receive a certificate of completion from Gdańsk University of Technology – the top technical university in Poland.
• It’s asynchronous, you learn whenever it suits you, except for one live online webinar on January 29.
• The course was developed by leading experts, including Dr Aleksander Orłowski, Professor at Gdańsk Tech and Vice President of the Gdańsk Agglomeration Development Forum, and Alina Guzik, an award-winning EdTech product designer and Head of the EdTech Innovation Lab at the Faculty of Management and Economics, Gdańsk Tech.
• It uses proven teaching methods: microlearning (short, focused lessons), video learning, and problem-based learning.
• You get access to engaging multimedia: studio and outdoor video lectures from Gdańsk, podcasts, case studies, and key industry reports.
• You can learn with an AI tutor that helps you go beyond the core materials.
• You practice through interactive online tasks created in H5P.
• You learn together with others: discussion forums and peer review of assignments support sharing experiences and perspectives.

At the end of this course, you will learn:

Remembering:

• Define and explain the key principles and components of smart cities, including their technological infrastructure and policy frameworks.
• Identify the main technologies supporting smart city initiatives, such as IoT, big data, and real-time systems.

Understanding:

• Describe the role of smart mobility systems in improving urban transportation efficiency and sustainability.
• Understand how autonomous vehicles, electric mobility, and ride-sharing platforms are transforming urban transport networks.

Applying:

• Apply knowledge of smart mobility systems to analyse their effectiveness in solving real-world transportation challenges.
• Demonstrate how big data, IoT, and real-time data can be used in city resource management, such as traffic management and energy distribution.

Analysing:

• Analyse smart mobility systems by examining case studies of their implementation and impact on transportation.
• Break down the role of data-driven decision-making in urban governance, specifically in managing resources like public safety and traffic flow.

Evaluating:

• Critically evaluate the impact of emerging technologies, such as autonomous vehicles and electric mobility, on existing urban transport systems.
• Assess the effectiveness of various smart city initiatives, drawing from global case studies in energy use, public safety, and transportation management.

Creating:

• Design a conceptual smart city project that integrates mobility solutions, IoT technologies, and real-time data management for improved urban services.
• Develop strategies for implementing smart mobility systems that leverage big data to address city-specific transportation challenges.

No formal degree is required. The course is suitable for learners from different backgrounds who:

• feel comfortable learning in English (B2 level recommended),
• have a general understanding of how cities function (public services, transport, infrastructure),
• are interested in technology, data, or urban development.

Previous experience in data analysis, IT, or public administration is welcome but not mandatory.

The course is structured into five thematic modules:

1. Introduction This module presents the idea of smart cities and the goals of the course. Learners get an overview of key topics, examples from practice, and how smart city solutions can improve everyday life in urban areas.
2. Main concepts Here we explain the core concepts and terminology: smart city, urban innovation, data-driven decision-making, stakeholders in the city ecosystem, and basic models of smart city development.
3. Mobility This module focuses on smart urban mobility: public transport, shared mobility, traffic management, micromobility, and sustainable transport solutions. Learners see how data and technology support better mobility planning.
4. Data and cities In this part, learners explore how cities collect, store, and use data. Topics include urban data sources, open data, data platforms, privacy and ethics, and examples of data-driven city services.
5. Main challenges The final module discusses key challenges related to smart cities, such as governance, digital exclusion, financing, interoperability, and citizen trust. Learners reflect on risks, limitations, and responsible implementation of smart solutions.

The two-level mutual trust-based quality assurance scheme has been adopted:

• at the university level: Gdansk Tech has applied its internal quality assurance procedures and structures to the proposal of Smart City it submitted to ENHANCE and to its implementation - the related learning activities,
• at the Alliance level: the body composed of Education Officers has made decisions regarding the inclusion of Smart City proposed by Gdansk Tech to the Innovative Learning Campus part of the joint ENHANCE educational offer, based on the compliance with the formal requirements and ENHANCE goals.

The webinar will take place on January 23 at 11:00 a.m. CET) and will last for 1.5 hours.

To successfully complete the course, learners must:

• pass the final quiz,
• post at least one contribution to the discussion forum, and
• attend the live online webinar.

Participants will be admitted on a first-come, first-served basis until all places have been filled.

Duration / workload: Around 25 hours of learning.

The course takes place on the Gdańsk Tech e-learning platform.