IBM Coursera Data Science

The subject of this blog post is my final project for the Coursera IBM Data Science specialization. Before I begin — if you are interested in learning data science from scratch, I would recommend this program. The pace is slow to start, but the program is thorough and covers the topics very well.

I choose to emulate the role of a business consultant, hired by a client who is an aspiring business owner looking to open a coffee shop in Toronto.

The client is concerned about where to open, given coffee shops are quite popular and has hired my firm to consider in greater detail two separate Toronto neighbourhoods that are under serious consideration.

One neighbourhood is in the heart of downtown Toronto, which is accessible easily by subway and walking. But how fierce is the competition?

The second neighbourhood is in suburban Etobicoke; less accessible by transit as there is no subway, but there is a streetcar and it is surrounded by middle class housing with new condos being built. It is up and coming.

The criteria being examined are the number of venues in the neighbourhood, and the number of these venues that are already coffee shops. Maps are used to visualize the density of the venues in each neighbourhood.

The downtown location turned out to not be ideal; with over 70 total venues, there are 7 coffee shops within the 5km radius examined. That’s just too much.

The suburban neighbourhood turned out to be a better choice; there are by a wide margin many less venues, but there is only 1 coffee shop allowing our client to establish a boutique brand without fear of strong competition.

The recommendation to the client would be to open in the Etobicoke neighbourhood of Alderwood.