Coursework: Computing for Analytics using Python: The course covered applied part of python used to do data analysis using machine learning algorithms.
To understand and compare the city’s demographics with its crime rate, analyse crime trends by crime type and explain the dependence of crime incidence to a varying number of factors.
The data relating to crime incidences recorded in Boston between 2015 and 2018 was obtained from Kaggle (“Crimes in Boston | Kaggle”), an extensive data resource reputed especially for its analytics competitions.
The study of Boston’s crime data starts with an exploratory analysis, which uses visual methods such as box plots, histograms and scatter plots to provide a snapshot of the relationships between various groups of independent and dependent variables. Post the exploratory analysis, analytical techniques such as regression analysis and K-means clustering further help identify possible correlations and identify groups organically.