The course provides a systematic overview both about intelligent methods used throughout the data analysis process and about intelligent, complex machine learning schemes used in modern data analysis. Unifying themes of this dual approach, are the Bayesian decision theoretic framework, the network and systems-based approaches, data and knowledge fusion, the use of ontologies and semantic technologies and active, online (reinforcement) learning, which integrate various phases and aspects of data analysis. The course also presents and discusses real-world applications, from the field of biomedicine, pharmaceutical research and system diagnostics.