In this module, students get hands-on experience using business analytics technologies in Python to generate tangible benefits.
We start by building the tools to gather data, focusing on web scraping and social media APIs.
Students then familiarize themselves with typical technologies used for descriptive, predictive, and prescriptive analytics.
To this aim, we build on real use cases in People and Marketing Analytics.
Building on their experience applying business analytics to real problems, we delve deeper into the Deep Learning and Reinforcement Learning toolbox.
Students get to know the background of many state-of-the-art machine learning tools and how to apply these tools in practice to generate tangible benefits.
While we continue building on some of the use cases in People and Marketing Analytics introduced previously, students also familiarize themselves with key finance and insurance management applications, among others.
Teaching at INSEAD
Below you can find an overview of my teaching experience at INSEAD.
Foundations of Informatics I, Industrial Engineering undergraduate core course on the basic concepts of computer science and software engineering
Classroom instructor for tutorials on object-oriented modelling, logic, algorithms, complexity theory, and dynamic data structures
Grading of exams
Foundations of Informatics II, Industrial Engineering undergraduate core course on theoretical computer science and computer architectures
Classroom instructor for tutorials on automata, computer architecture, formal languages, operating systems and modes, and data organization and management