Only if you complete all three days, you will receive a certificate
Content:
Discussion on previous week's home work. Please bring laptop with R/Python installed with you
We’ll walk through the Data Science Lifecycle using illustrative examples:
- Business Understanding – Defining the problem and setting goals
- Data Understanding – Exploration and analysis
- Data Preparation – Data cleaning and feature engineering
- Modelling – Selecting and training ML models (building on Lecture 1)
- Evaluation – Quality control and model performance
- Deployment – Making results accessible and usable
Level: Designed for those wanting a deeper dive into real-world, data-driven workflows.
We will do excercises and home work, which we will discuss on the next session
