July 20 – 28, 2024
Predeal, Romania
Organized by Bucharest University of Economic Studies, in collaboration with the GATE Institute at Sofia University “St. Kliment Ohridski” and the projects enRichMyData, Graph-Massivizer, UPCAST, INTEND, and InterTwino.
with the support of
Goal
The goal of the summer school is to familiarize students with relevant state of the art topics in data science and artificial intelligence (AI). The program will cover fundamentals of data science and AI and focus on the following key topics:
- Data analytics and statistics
- Machine learning and deep learning
- Large Language Models and Conversational AI
- Causal AI
- Time series and graph data
- Data sharing
- Data and AI pipelines (data enrichment pipelines, machine learning pipelines)
The program will consist of a combination of lecture-style talks introducing various data science paradigms and methods, and demo/hands-on sessions. The summer school aims to have a practical orientation, with Python and Jupyter Notebooks being used to exemplify many of the topics covered at the summer school.
At the end of the summer school, the students are expected to have an understanding of key paradigms used in data science and AI and be able to practically apply them in data science and AI projects.
Prerequisites
Familiarity with computer programming and basic knowledge about Python, interest in working with data, enthusiasm, and willingness to learn new things!
Basic knowledge of linear algebra, probability theory, and knowledge representation would be useful, though not strictly necessary.
