Predictive Analytics and Big Data

Schulich Executive Learning Centre

What are the topics?

Schulich Executive Learning Centre

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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.

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Who should attend

This program has been designed for executives and professionals with diverse needs from any sector or functional area, including managers who:

  • Want to learn data analytics tools and techniques and leverage insights from big data to allow their organization to make better business decisions
  • Are tasked with implementing, enhancing or expanding the role of analytics in their organization
  • Currently work on analytics projects or are involved with a data team, and want to increase their fluency in the domain and their command of its tools and techniques
  • Require a data analytics certificate to enhance their skill set

About the course

Data Visualization with Tableau

The rate at which data is generated and managed has increased exponentially in today’s information-based economy. Data visualization is both an art and a science which seeks to communicate information clearly and efficiently to users in an abstracted, schematic form. In this session participants will use visually interactive Tableau software to quickly:

  • Differentiate between statistical graphics, plots, information graphics, tables, and charts
  • Analyze, develop insights, and make conclusions about data and evidence
  • Make complex data more accessible, understandable and usable
  • Choose the most effective visualization technique for the task at hand

Data Science

Data Science extracts knowledge or insights from data in various forms and clearly communicates these findings to clients and end-users. Participants will be introduced to the field to data science, including current and future trends, intended business applications, and major technical categories. Through case analyses, participants will learn a comprehensive set of metrics to assess the precision of their analysis and tools to make statistically sound decisions.

  • The essential elements of any successful data science project
  • How to prepare analytical reports and project proposals
  • Evaluation metrics, and how to understand performance graphs
  • How to distinguish superficial results from truly meaningful information
  • Recommendation system, (i.e. Netflix), and online targeted display (i.e. Amazon recommendation system) case studies

Introduction to Regression Analysis

As organizations collect more data through advances in technology, business managers have improved opportunities to make data-driven decisions. This module teaches participants how to use regression analysis to identify the relationships between different business and data variables and make future predictions with statistical support.

  • How to use regression analysis in your organization
  • Identifying what variables will predict an outcome in a particular population or data segment

Experts

Diana Kawarsky

Biography Diana Kawarsky specializes in business communications for Schulich’s Executive Education Centre, York University. In addition, she is a facilitator, adult educator, coach and management consultant with Fortune 500 companies throughout North America. Her experience spans nearly 20 years...

Murat Kristal

Murat Kristal, PhD, is an associate professor of operations management at Schulich School of Business at York University. He teaches in the areas of business operations strategy, channel management and customer modeling. Dr. Kristal received his PhD from the Kenan-Flagler Business School at Unive...

Megan Mitchell

Biography Program Director, Centre of Excellence in Innovation Management, author and founding partner of Mitchell Consulting. Megan is one of Canada’s top innovation practitioners with over 20 years experience in innovation, marketing, sales, HR and leadership. Her passion is leadership effecti...

David Elsner

Biography David is the President of DHE Consulting where he leverages over 20 years of experience working with leading organizations across industries, helping guide them to make use of their data assets and providing solution implementation. An experienced lecturer and trainer, David provides a...

Ikjyot Singh Kohli

Ikjyot completed his undergraduate education in physics and mathematics at the University of Toronto. Following this, he obtained both his master’s and PhD degrees in mathematical physics from York University specializing in General Relativity and Dynamical systems. Ikjyot developed a passion for...

George Georgopolous

Dr. George J. Georgopoulos is from London Ontario. He received his undergraduate degree in Economics from the University of Western Ontario, M.A. and PhD in Economics from the University of Toronto, where he is now an Associate Professor of Economics at York University. He is also the Graduate Pr...

Keith Loo

Keith is a scale-up adviser and venture builder who advises high-potential, high-scale businesses on their technology, revenue and go-to-market strategies. He is heavily involved in the Canadian tech start-up community, and mentors, consults, and advises out of several incubators and accelerators...

Eugene Roman

Principle at Design AI Ltd. Advising companies on digital sustainability and unlocking moneyballs. Eugene previously held the position of Executive Vice‐President, Digital Excellence and Technology Advisor, for Canadian Tire Corporation (CTC). Eugene started his career in telecommunications and h...

Hemant Sangwan

Hemant Sangwan (PhD-Business, University of Toronto) is a professor of marketing at Seneca College and also affiliated with Master in Business Analytics (MBAN) program and the Schulich Executive Education Centre (SEEC) at Schulich School of Business at York University. His teaching assignments in...

Predictive Analytics and Big Data at Schulich Executive Learning Centre

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Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.