CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the dat
CS-421: Machine learning for behavioral dataComputer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will co
BIOENG-606: EDCB seminar seriesThe EDCB seminar series provides EDCB students the opportunity to share their research and learn from their peers. Students can freely exchange, present data, ideas and get useful feedback on ongoing
BIO-603(LG): Practical - LaManno LabGive students a feel for how single-cell genomics datasets are analyzed from raw data to data interpretation. Different steps of the analysis will be demonstrated and the most common statistical and b
CH-200: Practical programming in ChemistryThis course offers a comprehensive, practical introduction to computer programming tailored for chemists and chemical engineers. Python is the main language used throughout the course.
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
MGT-644: Conducting Qualitative ResearchThis workshop will expose you to a combination of readings, discussions, and hands-on exercises aimed at cementing your
understanding of, and ability to conduct qualitative research - especially gathe
ME-301: Measurement techniquesTheoretical and practical course on experimental techniques for observation and measurement of physical variables such as force, strain, temperature, flow velocity, structural deformation and vibratio
CS-448: Sublinear algorithms for big data analysisIn this course we will define rigorous mathematical models for computing on large datasets, cover main algorithmic techniques that have been developed for sublinear (e.g. faster than linear time) data
FIN-525: Financial big dataThe course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to fi