IAAC’s Master in City & Technology (1 or 2-year program) is a unique program oriented towards redefining the analysis, planning, and design of twenty-first-century cities and beyond. The program offers expertise in the design of digitally enhanced, ecological and human-centered urban environments by intersecting the disciplines of urbanism and data science. Taking place in Barcelona, the capital of urbanism, the Master in City & Technology is training the professionals that city administrations, governments, industries, and communities need, to transform the urban environment in the era of big data.


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Machine learning model to predict NYC cabs’ trip duration

Goal: to predict trip duration of NYC cabs using machine learning models. Tools: Python + Nympy + Pandas + Datetime + Plotly.express + Matplotlib + Math + Seaborn + Bokeh + Sklearn Stages of project: data cleaning, data analysis, data preparation, data testing, evaluating prediction accuracy. Data cleaning The first dataset visualization with splitting datasets … Read more

Data-Driven Rides

Machine Learning-based Analysis of NYC Cab Trip Duration “Data-Driven Rides” is an entry for the first MaCT Machine Learning Competition that hosted on Kaggle which involves predicting the duration of taxi rides in New York City. The dataset provided for this competition is based on the 2016 NYC Yellow Cab trip record dataset and the … Read more

Predicting NYC Cab Ride Duration using ML

The MaCT01 students were tasked with training a model that would be used to predict NYC yellow taxi ride durations using machine learning. The dataset included pickup and drop-off datetimes, location coordinates and passenger count. Visualizing the data helped to understand the correlation between the columns and remove the highly correlated values Understanding the distribution … Read more

2016 NYC Yellow Cab trip

The source dataset provided for this project is derived from the 2016 NYC Yellow Cab trip records, which were made publicly available on the Big Query platform of the Google Cloud. The data was originally collected and published by the New York City Taxi and Limousine Commission (TLC). This dataset serves as the foundation for … Read more

1st Traditional IAAC MaCT ML Competition

#Objective #A Kaggle Competition to MaCT01 students to show their knowledge, designing an end-to-end machine learning project to predict the “Trip Duration” of NYC Taxi trips. #Workflow #First of all a workflow hast do be developed, which represents a classic approach for training machine learning models, analysing the provided training data provided by the submission, … Read more

NYC Cab Trip Duration Prediction

The aim of the project is to predict trip duration, using 2016 NYC YELLOW CAB TRIP DATA. Structuring the dataset The analysis begins with outlier identification. The passenger_count variable has two outliers: 0 and 9, which compared to the amount of people allowed by the NY Limousine law, is impossible. Also, there were some pickup … Read more

Gridscape.ai

INTRODUCTION Urban planning decisions have a significant impact on the development of cities, and using machine learning can provide decision-makers with valuable insights to make informed decisions. By clustering urban areas based on various factors such as population density, built density, POI density, green cover, and build diversity, we can reveal spatial patterns that can … Read more

Meteo sanctum

The project reflects on how people in ancient times defined natural and weather phenomena. The proposal is to create an open public space – Inspired by the concept of an ancient sanctuary with places that used to be built for worship and predictions of weather conditions, the Meteo Sanctum consists of digital indicators that allow … Read more

Stickers in Barcelona, el Gotico

Objective The objective of the project is to create a database of stickers located in the district of Gotico, Barcelona by collecting geolocated photos, analyzing & sorting them by machine learning and further research to then create a framework for evaluating and improving local economy, artists and political movements marketing strategies. Strategy By collecting geolocated … Read more

Dislocating Creativity

“A Data-Driven Approach to Balancing Creative Class Development and Social Equity in Barcelona” The creative industries have been acknowledged as one of the most important sectors for economic growth and development in current cities worldwide. This sector represents a space of culture where all artistic and creative expression that pro-actively enters into dialogue with new … Read more

A Policy for Digital Carbon Footprint, Barcelona

Every single search query, every streamed song or video and every email sent, billions of times over all around the world – it all adds up to an ever-increasing global demand for electricity, and to rising CO2 emissions too. Our increasing reliance on digital tools has an environmental impact that’s becoming increasingly harder to ignore. … Read more

A Parallel City for Pollinators

Introduction to Pollination The project attempts to study and research the possibilities of creating a green, three-dimensional corridor for pollinators in a specific area, the historical city center of Madrid, connecting Madrid’s most prominent green park “el Retiro” in the east to the “Casa de Campo” natural reserve in the west. In particular the proposal … Read more