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Deep Learning in Data Science

  • 7.5 credits

You will learn to

• explain the basic the ideas behind learning, representation, and recognition of raw data,

• account for the theoretical background for the methods for deep learning that are most common in practical contexts,

• identify the practical applications in different fields of data science where methods for deep learning can be efficient (with special focus on computer vision and language technology).

Only students from the following programmes can apply: Master's Programme in Mathematical Statistics, Master's Programme in Actuarial Mathematics, and Bachelor's Programme in Computer Science.

Further course information will appear soon on this page. Until then, information can be found on the department website.