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.
Undertaken by: Avi Sharma Hypothesis : Exposure to Music correlates with variations in Mental Health among people. We all know that listening to music can evoke various emotions, depending on the song. What I am exploring is the idea that exposure to music, in general, can play a role in shaping your overall mental health … Read more
Main question. How built heritage affects real estate market in European cities? Hypothesis Let’s look at this question on the example of Barcelona. Let’s single out the city neighborhoods (barrios) where historical buildings are located, and analyze the ratio of average real estate prices to them, in particular, the sale prices of apartments and houses. … Read more
The city of Mumbai, known as the financial and entertainment capital of India, has experienced a significant surge in housing prices and rents in recent years. The demand for residential properties in Mumbai has been steadily increasing due to factors such as population growth, urbanization, and the city’s thriving job market. In the midst of … Read more
The New York City Taxi Trip Duration competition is a challenge to develop a model that predicts the total ride time of taxi trips in New York City. Yellow medallion taxicabs, which number 12,779 in New York City, generate a substantial revenue of $1.8 billion per year by providing transportation services to around 240 million … Read more
The objective of this exercise is to build a machine learning model that will predict taxicab trip durations based on 2016 NYC Yellow Cab trip record data. Data Fields Based on this, this project will develop a machine learning regression algorithm capable of predicting the duration of a trip based on the variables provided by … Read more
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
