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In this course, students will learn how to apply Supervised, Unsupervised and Reinforcement Learning techniques for solving a range of data science problems.

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.

This online course gives an introduction to developing deep learning models with Tensorflow (an open source machine library for deep learning).

This online course teaches how to to create machine learning algorithms in Python and R.

This course teaches concepts of machine learning. Machine learning engineers build programs that dynamically perform the analyses that data scientists used to perform manually....

This series of online courses (MOOCs) teaches Data Science using the Python programming language.The courses explore how to apply statistical, machine learning, information...

This online course teaches the foundations of deep learning. Participants can learn how to build, train and apply deep neural networks.

How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class these two seemingly...

This online video lecture series gives an introduction to Reinforcement Learning.

This online lecture discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods.

Dieser Online-Kurs erläutert die Grundlagen der Programmierung mit Python für Anwendungen im Bereich Data Science.

Dieser Online-Kurs gibt eine Einführung ins Machine Learning für Data Science-Anwendungen, inklusive Regression, Klassifizierung und Clustering. Dafür werden Anwendungen sowohl...

Dieser Online-Kurs zeigt, wie Machine Learning-Projekte in der Praxis umgesetzt werden. Vorkenntnisse der Grundlagen von KI und Maschinellem Lernen sind dabei erforderlich. Die...

Dieser Online-Kurs erläutert die Grundlagen von R und R-Studio für Data Science-Anwendungen.

Dieser Online-Kurs erläutert die Grundlagen des Maschinellen Lernens inkl. des Reinforcement Learning. Gewisse Vorkenntnisse in der Programmierung sind hilfreich.