Artificial Neural Networks and Deep LearningSemester Course

DIS Copenhagen, Core Course, Artificial Neural Networks and Deep Learning DIS Copenhagen, Core Course, Artificial Neural Networks and Deep Learning DIS Copenhagen, Core Course, Artificial Neural Networks and Deep Learning DIS Copenhagen, Core Course, Artificial Neural Networks and Deep Learning DIS Copenhagen, Core Course, Artificial Neural Networks and Deep Learning
Program
Computer Science
Week-Long Study Tour
London
Core Course Week Study Tour
Denmark
Major Discipline(s)
Computer Science, Information Science, Mathematics
Type
Core Course
Available
Fall/Spring semester
Credit(s)
3

Artificial Neural Networks are programs that write themselves when given an objective, some training data, and abundant computing power. Recently, these programs have brought about a wide array of impressive innovations, such as self-driving cars, face recognition, and human-like speech generators. This course offers you an introduction to Deep Artificial Neural Networks (i.e. “Deep Learning”). With focus on both theory and practice, we cover models for various applications, how they are trained and tested, and how they can be deployed in real-world applications

Related Discipline(s)

This course would also be of interest to the following discipline(s):
Computer Science

Faculty

Daniel Svendsen

DIS Copenhagen Semester Faculty

PhD in Electrical Engineering from the University of Valencia 2020. Research focused on the incorporation of physical knowledge in machine learning models. Data science consultant to various startups 2020 such as eeSea and Pensure. MSc in Mathematical modelling and computation from the Technical University of Denmark 2016. Teaching assistant in various courses 2015-2016. With DIS since 2021.

Lucian Leahu

DIS Copenhagen Semester Faculty

PhD in Computer Science from Cornell University 2012. Assistant professor at ITU Copenhagen since 2015. ERCIM Postdoctoral Fellow at the Swedish Institute of Computer Science (2012-2013) and Project Leader in the Media Technology and Interaction Design Department at the Royal Institute of Technology (2014). With DIS since 2019.

Nicolai Frost Kolborg Jacobsen

DIS Copenhagen Semester Faculty

Msc Dual Degree in Data Science, Technical University of Denmark & Korea Advanced Institute of science and technology. Worked as a statistician for the Meteorological Institute of Denmark. Data Science & BI consultant for IQVIA and currently lecturer at Copenhagen Business School and a Machine Learning Engineer & Manager at a Health Tech Startup. With DIS since 2022.

Ulrich Andreas Mortensen

DIS Copenhagen Semester Faculty

PhD in Mechanics and Material Science from the Technical University of Denmark. PostDoc Fellow at DTU Wind Energy. Research in Composite Materials and Materials Mechanics with focus in multi-physics Numerical Modelling of Materials Manufacturing. MSc in Engineering Design and Applied Mechanics from the Technical University of Denmark 2016. With DIS since 2022.

Peter Rasmussen

DIS Copenhagen Semester Faculty

Ph.D. in Computer Science, University of Copenhagen, Denmark (2021). Research focus on algorithms, in particular research in hashing algorithms, graph algorithms, graph theory, and computational geometry. Data Scientist, development and deployment of machine learning algorithms, Halfspace, Copenhagen, Denmark (2021-2022). With DIS since 2023.