EXECUTIVE EDUCATION
EXECUTIVE EDUCATION
March 4, 2021
6 weeks, online
4-6 hours/week
Special pricing up to 20% discount is available if you enrol with your colleagues. Please send an email to group-enrollments@emeritus.org for more information.
Analyzing data and putting it to work for you and your business is an essential skill for executives today. But if you are not as fluent as you need to be in data and analytics, you’re not alone. According to The Data Literacy Index from Qlik, just 24 percent of the global workforce feels confident in reading, working with, analyzing, and arguing with data. You can close that competency gap by gaining the skills to transform your organization into a data-driven enterprise.
This is not just about adding to your own professional skill set. Gartner reports that 80 percent of organizational leaders have a goal of initiating a deliberate plan to improve the data literacy of their workforce at large. Position yourself and your company to advance your data literacy and confidently lead a data-driven corporate culture.
Source: The Financial Times 2020
Each module is designed to help you craft the narrative for your company’s data literacy by improving your own data fluency and gaining an understanding of the business value quality data and expert analytics can create for your business.
Dive into the fundamentals by comparing the various types of data analysis, examining variables, and analyzing the impact of sample size and sample bias.
Do you know your dashboards? Understand the applications of data analytics dashboards and the use of conditional averages, distributions, regression to the mean, and hypothesis testing to devise Key Performance Indicators (KPIs)
If futurecasting appeals to your strategic side, it’s critical to understand predictive analysis, the construction of a prediction model, the application of machine learning and AI to prediction, and the strategic implications of prediction.
Perhaps the single most essential tool in statistical modeling, regression is central to data literacy. Learn what regression does, how it fits into prediction, and what questions to ask data analysts (and yourself).
How do you mold raw data into a business strategy? Examine cause and effect in data analysis, design an experiment, analyze causal inference without experiments, and be prepared to prescribe a response to the likely results.
Widen your view of data literacy to your whole workforce. Develop an organizational model for a question-driven approach to data analysis, understand privacy concerns, and formulate a strategy to build an evidence- and learning-based corporate culture.
Dive into the fundamentals by comparing the various types of data analysis, examining variables, and analyzing the impact of sample size and sample bias.
Perhaps the single most essential tool in statistical modeling, regression is central to data literacy. Learn what regression does, how it fits into prediction, and what questions to ask data analysts (and yourself).
Do you know your dashboards? Understand the applications of data analytics dashboards and the use of conditional averages, distributions, regression to the mean, and hypothesis testing to devise Key Performance Indicators (KPIs)
How do you mold raw data into a business strategy? Examine cause and effect in data analysis, design an experiment, analyze causal inference without experiments, and be prepared to prescribe a response to the likely results.
If futurecasting appeals to your strategic side, it’s critical to understand predictive analysis, the construction of a prediction model, the application of machine learning and AI to prediction, and the strategic implications of prediction.
Widen your view of data literacy to your whole workforce. Develop an organizational model for a question-driven approach to data analysis, understand privacy concerns, and formulate a strategy to build an evidence- and learning-based corporate culture.
Try-it activities
Peer discussion groups
Crowdsourcing activities
Quizzes
Real-world applications assignments
Live Webinar
As Rotman Chair in Artificial Intelligence and Healthcare and Professor of Marketing at University of Toronto’s Rotman School of Management, Avi Goldfarb’s research focuses on the opportunities and challenges of the digital economy. Along with Ajay Agrawal and Joshua Gans, Dr. Goldfarb is the author of The Globe and Mail bestselling book Prediction Machines: The Simple Economics of Artificial Intelligence. He has published more than 70 academic articles in a variety of outlets on the topics of marketing, statistics, law, computing, and economics. This work has been discussed in White House reports, Congressional testimony, European Commission documents, The Economist, The Globe and Mail, the National Post, CBC Radio, National Public Radio, Forbes, Fortune, The Atlantic, The New York Times, the Financial Times, The Wall Street Journal, and elsewhere.
Dr. Goldfarb holds a Ph.D. and M.A. in Economics from Northwestern University and a B.A. in Economics from Queen’s University.
Upon successful completion of the program, you’ll earn a digital certificate of completion from the Rotman School of Management. This program counts toward a Rotman Excellence in Executive Leadership Certificate.
Download BrochureNote: All certificate images are for illustrative purposes only and may be subject to change at the discretion of the Rotman School of Management.
Flexible payment options available.
