Data Analysis is a mathematical discipline and students will benefit from a good background in probability, linear algebra and calculus. Programming capabilities, previous knowledge of SQL and Python will help, but they are not mandatory.
Provide to students the methodologies and the technological tools for implementing data analyses for business analytics.
This course is designed for students with strong aptitude in mathematical, statistical and computational disciplines and interested in working with data. Students will learn - by means of the solutions of real business cases - the techniques at the state of the art of exploratory data analysis, data-driven modeling and optimization.
Each lesson will cover a specific topic both with theoretical and practical perspectives. At the end of the course, the students will be able to solve independently standard problems with industry-standard technology and they will have the principles to manage a data analytics team.
The course also includes two seminars where top professionals who are leading data analytics teams will share their experience.
Lectures with slides and in-depth discussions on the whiteboard.
Demonstration of state-of-the-art tools for the data analytics (e.g. interactive notebooks, Tableau).
Solutions of business cases interactively through the use of interactive notebooks (Google Colab) and Business Intelligence tools (Tableau).
Final written exam of 2 hours. Oral exam optional (access mode to be defined).