Fundamentals of Data Science
Sapienza University of Rome · M.Sc. in Data Science
Overview
This course introduces the foundational tools of data science, combining machine learning, statistical modeling, and network science.
Students learn how to treat data as a strategic asset, moving from data representation and preprocessing to model design, training, and evaluation.
Main objectives
- Understand the core principles of machine learning foundations (regression, classification, neural networks, CNNs, transformers, multimodal ML)
- Explore complex networks and network science (network properties, generative models, community detection)
- Practice hands-on Python programming for data analysis and modeling
Learning outcomes
- Ability to design and evaluate discriminative and generative models
- Translate complex phenomena into formal ML and network frameworks
- Communicate results through visualizations, metrics, and project presentations
- Develop autonomy to extend skills to computer vision, network science, and advanced ML
My work in this course
- Notes & Exercises
- Final project