KTU Big Data School 2025

The program features intensive hands-on sessions, where participants will engage directly with key concepts in data science and machine learning. These sessions will cover a broad spectrum of topics, from foundational techniques to more advanced methodologies, ensuring that attendees acquire both theoretical understanding and practical proficiency. The sessions will be led by experienced professionals and academics, who will guide participants through real-world applications, enabling them to apply their learning in professional or academic contexts. 

We invite early career data scientists, engineers, and professionals to participate in a two-day KTU Big Data School dedicated to advancing knowledge and practical skills in data science and machine learning. This event is designed for students seeking deeper theoretical insights, industry professionals aiming to broaden their expertise, and individuals considering a transition into data-driven roles. The KTU Big Data School combines hands-on practical sessions with focused theoretical lectures, offering participants a comprehensive and applied learning experience. 

A significant portion of the KTU Big Data School will be dedicated to collaborative problem-solving. Participants will be organized into teams to address complex challenges proposed by industry partners. This collaborative approach is designed to simulate the professional environment of data science projects, fostering teamwork and the practical application of newly acquired skills. The challenges will provide participants with the opportunity to work collectively on real-world problems, enhancing both their technical abilities and collaborative competencies. 

Participants seeking academic recognition can opt for a 1.5 ECTS credit track, providing a formal acknowledgment of their learning and its application. In addition to the technical and collaborative learning experiences, the Winter School offers valuable networking opportunities, facilitating connections with peers, industry experts, and academics in the field of data science. This event represents a significant opportunity for professional development and academic advancement within the data science community.