All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.
All our activities include solutions with explanations on how they work and why we chose them.
Given a dataset containing customer demographics and purchase history, how can we group customers based on their similarities to tailor marketing strategies?
How can we identify unusual patterns or anomalies in network traffic that may indicate a security breach, without having prior labeled examples of such incidents?
Given historical data on housing prices and features such as location, size, and amenities, can we build a model to predict the prices of new houses?
Given customer feedback data on an e-commerce website where customers can rate their satisfaction on a scale from 1 to 5, should we model this problem as a classification or a regression task?