Applied Deep Learning for Scientists

TitleTimeRoomInstructor
Applied Deep Learning for Scientists26.02.2024 10:15 - 11:30 (Mon)Moonstone Bldg / O2 / Office Meeting Room (I24.O2.026)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists28.02.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)28.02.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists04.03.2024 10:15 - 11:30 (Mon)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists06.03.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)06.03.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists11.03.2024 10:15 - 11:30 (Mon)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists13.03.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)13.03.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists18.03.2024 10:15 - 11:30 (Mon)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists20.03.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)20.03.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists (recitation)27.03.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists03.04.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)03.04.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists08.04.2024 10:15 - 11:30 (Mon)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists10.04.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)10.04.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Applied Deep Learning for Scientists15.04.2024 10:15 - 11:30 (Mon)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists17.04.2024 10:15 - 11:30 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)Bronstein, Alexander
Locatello, Francesco
Applied Deep Learning for Scientists (recitation)17.04.2024 11:45 - 12:45 (Wed)Sunstone Bldg / Ground floor / Big Seminar Room B / 63 seats (I23.EG.102)
Description: 
Deep learning is a powerful and relatively new branch of machine learning. In recent years, it has been successfully applied to some of the most challenging problems in the broad field of AI. After beating human champions in complex games like go and chess, achieving impressive levels in machine translation and conversational skills, generating photo-realistic images, and predicting protein structures at unprecedented levels of accuracy, deep learning is becoming the natural tool of choice for a broad range of data-driven scientific applications. This course will focus on practices of modern deep learning with a focus on tools and applications in life and physical sciences. It is a graduate-level introduction course that provides both the necessary theoretical background and the hands-on experience required to be an effective deep learning practitioner or to start on the path toward deep learning research.
Capacity: 
8/15
Course Code: 
C_DSSC-4001_S24
Course instructor(s): 
Alexander Bronstein
Francesco Locatello
Main Contact: 
Francesco Locatello
Course type: 
Taught course
Course tags: 
Elective
Course level: 
Advanced/specialized
Primary Track: 
Data Science & Scientific Computing
Secondary Track(s): 
Computer Science
Course format: 
On campus
Classroom requirements: 
Whiteboard
Projector
Duration: 
Half semester
ECTS: 
3
Semester: 
Spring 1
Target audience: 
Graduate students and postdocs across the campus.
Prerequisites: 
Multivariate calculus, linear algebra, probability theory.
Teaching format: 
Lectures + recitations
Assessment form(s): 
Home assignments + final project
Grading scheme: 
Numeric grades (1-5)
Course Category: 
Credit Course
Academic Year: 
AY 2023/24