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DTU Course - Advanced Business Analytics / Advanced Data Science (2020)

Business Analytics (BA) is about exploring and analysing large amounts of data to gain insight into past business performance in order to guide future business planning. This course introduces a portfolio of advanced data-centric methods which cover the three main directions in BA: Descriptive (“what happened?”), predictive (“what will happen?”), and prescriptive (“what should happen?”). The methods will be applied to various business cases with the aim to demonstrate how to extract business value from data, provide data-driven decision support along with effective data management principles.

Course Content (Selected Lectures)

  • Refreshing Python and Machine Learning (Python, Jupyter notebooks, Numpy, Matplotlib, Pandas, machine learning with scikit-learn)
  • Web data mining (APIs, web scrapping)
  • Text analytics (text processing, information retrieval, topic modelling)
  • Recommender systems
  • Network analysis
  • Introduction to deep learning
  • Uncertainty in predictive modelling (probability calibration in classification, uncertainty estimation in regression, quantile regression)
  • Interpretable machine learning (explainable AI, model-specific and model-agnostic approaches, global and local interpretability)
  • Performance metrics and business thinking (communicating data science results, performance metrics for regression and classification)

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DTU Course - Advanced Business Analytics / Advanced Data Science (2020)

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