Applications of Data Science (Computational Projects)
This course serves as a companion to the 'Mathematical Foundations of AI' lecture, providing practical applications of the topics discussed therein. Through this course, students will learn to approach data science challenges with a methodological and mathematically sound framework while gaining hands-on experience in tackling real-world problems.
In today's rapidly advancing fields such as biology, chemistry, and medicine, cutting-edge technologies are generating vast amounts of data with unprecedented levels of detail, accuracy, and breadth. Analyzing this data holds the promise of gaining new insights, yet it also presents significant challenges for data scientists. These two lectures together equip students with the essential theoretical understanding and practical skills necessary to navigate these challenges. State-of-the-art methods from machine learning, data processing and analysis will prepare participants as data scientists for coping with a broad range of problems in both research and industry.
Equipped with the knowledge acquired from the lectures, students can readily initiate internships or research projects within the groups working in data science at the Institute of Mathematics or CAAPS.
