Translating Data Science into Leadership Decisions

Big data has become an integral part of strategic management. Learn how to translate the raw numbers and complex reports into content you can use to make evidence-based executive decisions. This one-day workshop led by Dr. Ceni Babaoglu and Dr. Ayse Bener will give you an overview of data science, an introduction to data models and tools used by data scientists, and a fundamental understanding of how to work with data scientists to make the data work for you.

What's in it for you?

  • A comprehensive overview of data science and the skills required by data scientists
  • An introduction to data analytics
  • An overview of statistical tools for data analytics (such as R)
  • Other tools for data analytics (for structured and unstructured data)
  • A demonstration of machine learning methods
  • Practice modelling and reporting results

Facilitators

Dr. Ceni Babaoglu is a Senior Data Analytics Associate at The Chang School and Data Science Instructor at Ryerson University. Since receiving her PhD in Applied Mathematics from Istanbul Technical University, she has worked as a researcher and Mathematics instructor in Istanbul, Sweden, and Toronto. Four years ago, inspired after visiting a Data Science Laboratory – where she learned the practical applications of data analytics and how it involved (her specialty) mathematics – Ceni shifted her focus to data. Her current research is focused on numerical analysis, data mining, and machine learning programming. She is also an associate member of the Yeates School of Graduate Studies at Ryerson University and co-supervises the major research projects of Data Science and Analytics M.Sc. students.

Dr. Ayse Basar Bener is a professor and the director of Data Science Laboratory (DSL) in the Department of Mechanical and Industrial Engineering, Ryerson University. She is the director of Big Data in the Office of Provost and Vice President Academic at Ryerson University. She is also the Program Director of both Certificate Program in Data Analytics, Big Data, and Predictive Analytics, and the Master of Science Program in Data Science and Analytics at Ryerson University. She is a faculty research fellow of IBM Toronto Labs Centre for Advance Studies, and affiliate research scientist in St. Michael’s Hospital in Toronto. Her current research focus is big data applications to tackle the problem of decision-making under uncertainty by using machine learning methods and graph theory to analyze complex structures in big data to build recommender systems and predictive models. She is a member of AAAI, INFORMS, AIS, and senior member of IEEE.

Admission Criteria

There are no academic prerequisites for enrolment. However, please note that participants will be expected to engage in case studies and group discussions and, as such, should have the appropriate level of work experience. This workshop is designed for executives, consultants, and senior managers.

Format

Concepts will be presented using activities, case studies, and data analytics scenarios.

For More Information

For more information about this workshop, contact Brigid Elmy, Special Projects Officer, Business Development and Strategic Planning, at belmy@ryerson.ca.