Bruno & Co. have come up with a business use-case to predict customer churn using sales data! They will use survival analysis and Python to answer the question: "What is the probability you will retain your customer in a week? In a month? And so on..."
This month’s Data Science club meeting is geared towards mid-level developers and requires the attendees to program in a Kaggle notebook. Interactivity here is key. Be prepared for some back-and-forth with the presenter. Here is a link to Kaggle to make an account.
For n00bs to get familiar with Kaggle or Python, here is a great free resource that gets you through basic Python. After that, you can explore data science in these courses (Bruno recommends Pandas):
1. https://www.kaggle.com/learn/overview
Here are the two datasets the group will use at this month’s meeting:
1. https://www.kaggle.com/blastchar/telco-customer-churn
2. https://www.kaggle.com/carrie1/ecommerce-data/home
And a good notebook that you can copy and edit:
1. https://www.kaggle.com/pavanraj159/telecom-customer-churn-prediction
Please go ahead and register an account with Kaggle before the meeting time. Get familiar with the environment, as this will enable everyone to get started faster.
Non-programmers might find value in seeing a real-world example of how programming can answer business questions, but it will be best received if they are already interested in programming.
This is the virtual meeting link of the Data Science Club based out of theClubhou.se. The purpose of the group is to delve into data science using Python. The group meets on the first Thursday of every month.