In this assignment, you will take the role of a real-world data scientist tasked to identify areas to direct investments. You are consulting for the City of Liverpool on a program to target investments towards particularly disadvantaged areas that are nevertheless popular or have the potential to become so. The Economic Development division knows that only five local super output areas (LSOAs) will be funded but would like to know which ones.
Choose one of the given questions, develop a data strategy, deploy it, and present the results in a rigorous but intuitive fashion, together with the code.
Minimum requirements (complete all)
Combine at least two datasets, potentially among those used in the course.
Employ at least two techniques from the set of analytics covered in the course.
Justify why you have chosen the methods you use and how they help you answer the question at hand. Critically discuss their limitations too.
Provide a list of the top five areas that you recommend be funded for improvement.
Explain clearly how you have arrived at the list and how the decision has been informed by the data analysis and the methodologies employed.
Include documented code and data that allow the replication of the analysis presented.
Assignments will be prepared in the Jupyter Notebook file format and then converted into a self-contained HTML file.