Welcome to my GitHub repository for my Master's program in Fundamental Principles of Data Science at UB. Here, you'll find a collection of my coursework and projects from my studies. This repository is a comprehensive showcase of my work, reflecting my commitment to mastering the core foundations and principles across various areas of Data Science.
Large amounts of data are generated in many aspects of personal and professional life, from electronic purchases to research or finances. If these data are not monitored or interpreted, they have no value. Data science is a new professional area that aims to give these data meaning by analyzing and interpreting them. A data scientist is a new professional profile at the intersection between maths and computer science.
The master’s degree in Fundamental Principles of Data Science aims to provide, through theoretical and practical training, the algorithmic and mathematical bases for correct modeling and analysis of data, and the professional competencies to face data-based projects. There is a focus on competencies to understand the principles of algorithms that lie behind data science. Students will develop the ability to modify algorithms and create new ones, to adapt to the specific needs of a problem.
Consequently, the course includes aspects that cover a wide area: computational algebra, optimization or probabilistic programming, automatic learning techniques and deep learning, complex networks, recommendation systems, applications to natural language processing, time series, extraction of information in images, and support for infrastructures that process big data.