Research Topics in Data Science
This course explores contemporary research in data science, focusing on recent advancements in machine learning and data mining.
Students will engage with cutting-edge research papers, emerging methodologies, and open challenges in the field. Topics include machine learning techniques and algorithms, covering developments in supervised, unsupervised and reinforcement learning, as well as novel deep learning and statistical methods.
The course also examines processes in data science research, including interpretability, reproducibility, and ethical considerations. Key challenges such as scalability, bias, fairness and robustness are discussed alongside methods for handling complex data structures.
Additionally, students will explore emerging trends and applications. Through research discussions, hands-on projects and presentations, students will critically analyse developments and identify open research questions. The course content is updated regularly to reflect the latest trends in data science.
Teaching Format
The teaching activities consist of lectures and seminars.
The language of instruction is English.
Assessment
The course is examined through assignments and presentation of research results.
Examiner
Study counsellors
Visiting hoursPlease contact us via email if you want to book a meeting. We are available on Campus in Kista and via Zoom.
Phone hoursThursday 12.30–2 pm
Irregular office hoursFirst phone hours for spring 2026: Thursday 15 January
