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
Stockholm or Berlin or Madrid-Valencia or 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

Ph.D in Electrical Engineering, University of Valencia (2020). Research focus on the incorporation of physical knowledge in machine learning models. Previous experience as a Data Science Consultant to various startups, such as eeSea and Pensure (2020). M.Sc. in Mathematical Modelling and Computation from the Technical University of Denmark (2016). Also taught as a Teaching Assistant in various courses (2015-2016). With DIS since 2021.

Lucian Leahu

DIS Copenhagen Semester Faculty

Ph.D. in Computer Science, Cornell University (2012). Previous experience as Assistant Professor at ITU Copenhagen (2015-2018), ERCIM Postdoctoral Fellow at the Swedish Institute of Computer Science (2012-2013),an 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

Head of Data Science at Corti (2019–present), leading a team to build a system that leverages Automatic Speech Recognition output to measure call quality. M.Sc. Dual Degree in Data Science, Technical University of Denmark & Korea Advanced Institute of Science and Technology (2017 and 2018, respectively). B.Sc. in Natural Science and IT, University of Copenhagen (2015).. Previous experience building forecasting models as Data Scientist at Scales (2018) and optimized equipment distribution with Python and integer programming as Business Intelligence Consultant at IQVIA (2015–2018). With DIS since 2022.

Ulrich Andreas Mortensen

DIS Copenhagen Semester Faculty

Ph.D. in Mechanics and Material Science, Technical University of Denmark (2019). Previous experience as Postdoctoral Fellow at DTU Wind Energy. Conducted research in Composite Materials and Materials Mechanics with focus on multi-physics Numerical Modelling of Materials Manufacturing. M.Sc. in Engineering Design and Applied Mechanics from the Technical University of Denmark (2016). With DIS since 2022.

Matthias Heumesser

DIS Copenhagen Semester Faculty

Ph.D. in Atmospheric Physics, Marie Skłodowska-Curie Fellow, Technical University of Denmark (2021). Currently leads development of custom car and charger integrations for a smart charging platform as Development Team Lead at True Energy A/S (2022–present). Previous experience developing NLP models for question and implied information detection in emergency calls as Software Developer at Corti (2021–2022). With DIS since 2023.