The Learning objective is to understand the impact of AI and Machine Learning on all aspects of life and the opportunities as well as risks associated with the digital disruption. The course covers the management perspective (concepts and end-user perspective) as well as the IT perspective (Implementation of AI and Machine Learning solutions).

The topics covered include:

• Use cases of AI/Machine Learning
• Business value
• Architectures and tools for AI/Machine Learning
• Data Science Lifecycle
• Discovery
• Data preparation (Extraction, transformation, load)
• Model planning
• Model building & evaluation
• Communication
• Analytical methods and models for machine learning
• Exploratory data analysis (descriptive, predictive)
• Clustering
• Association rules
• Regression
• Classification
• Time series analysis & Forecasting
• Text analysis
• Unstructured Data analysis
• Data visualization

The exercises are performed using a selection of tools from the following list: Python including the libraries of Scikit-Learn, TensorFlow and Keras.