As data sources grow along with the computational capabilities to process them, capitalizing on the data has become fundamental to the success of organizations. Machine learning has become a pillar in supporting decision makers in organizations across multiple fields. Whether anticipating if a customer is going to churn, a machine is going to fail or identifying a disease in an image; machine learning use cases are proving more and more crucial.

This course provides an overview of artificial intelligence, machine learning, data mining, and pattern recognition.  Case studies and applications will be used to highlight how to properly apply learning algorithms to building smart solutions, text understanding, computer vision, data base mining and other areas.  Upon completion of this hands-on course, participants will discuss a machine learning model solution which will give them experience in data preparation, model selection and testing in order to apply their skills on real world problems.  This will enhance the proficiency of the participants in identifying, formulating and testing potential solutions in their daily routines.

Skills Include:

  • How to convert the business challenges into ML experiments.
  • How to determine which features are essential for the model.
  • How to determine which algorithms are best to start with and how to tune them.

The program will also reinforce skills to help participants communicate technical information to peers, management and/or other key stakeholders in a way that fosters collaboration and facilitates the adoption and integration of new data solutions within the workplace.