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  1. Translating business problems into analytical questions
  2. Creating and evaluating data science algorithms
  3. Principles of supervised and unsupervised machine learning
  4. Introduction into artificial intelligence
  5. Introduction into the Python Anaconda framework


This hands-on module reflects an introduction to machine learning and artificial intelligence.  We will address fundamental concepts for data-driven decision making and data-analytical thinking by following a case-based approach. Using widespread and state-of-the-art tools for big data and artificial intelligence (e.g., Python Anaconda Framework), we provide an introduction into machine learning and artificial intelligence. Participants will get practical experiences in implementing and evaluating state-of-the-art algorithms for analyzing structured and unstructured data such as text. As opposed to most big data and artificial intelligence course, this module is not taught in a method-oriented fashion, but follows a case study logic – we choose a variety of real-world business problems and solve them the analytics way.

After the module, participants…

  • are familiar with the central terminology in the fields of machine learning and artificial intelligence

  • can translate business problems into analytical questions

  • can select, implement and evaluate common machine learning algorithms for a variety of analytical questions

  • can analyze structured and unstructured data (e.g., text)