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Who should attend
- Leaders who want to deepen their understanding of today’s digital transformation, including senior managers and executives launching data initiatives;
- Business intelligence and data managers, engineers and architects; and
- Business line executives who want to become more AI and analytics savvy.
About the course
Data-driven companies are harnessing the power of advanced analytics and artificial intelligence to make smarter decisions, optimize service and streamline operations. Where does your organization stand in its evolution?
Building the Intelligent Enterprise will help you embrace the imperatives of digital transformation, envision where your teams and organization need to be in 10 years—and map out the strategies and tactics to get them there.
In two high-powered days, expert-led interactive sessions will explore and demystify big data, data science and artificial intelligence’s latest iterations: machine learning and deep learning. You’ll explore the skills leaders need to drive digital transformation, harness data for results and lead an intelligent enterprise. You’ll understand how to select, manage and measure the impact of projects and strategies. You’ll explore ideas from leading thinkers about how the data revolution is reshaping society, culture and the nature of work. You’ll examine ethical implications as the use of advanced analytics and AI expands exponentially
- An understanding of Next Generation Analytics
- History of Data Science
- AI, Machine Learning and Deep Learning Overview; including
- - Hype versus Reality;
- - Drivers of Adoption;
- - State of the Industry; and
- - Barriers to Entry
- Building a Next Generation Analytics Organization; including
- - Organizing for AI, ML and DL;
- - Building Data Driven & Data Literate Organizations;
- - Critical Roles;
- - Innovation Cycles & Uncertainty; and
- - Maturity Models
- Getting Started with AI, ML and DL; including
- - First Projects & Evaluating Outcomes;
- - Deployment Models & Business Impact;
- - Managing Budgets; Mode 1/Mode 2 Technology Models;
- - Insourcing vs. Outsourcing; and
- - Program Management
- Long-Term Implications of ML & AI; including
- - Moving to Sustained Adoption;
- - Centralized vs. Decentralized Models;
- - Resource Retention;
- - Workforce Displacement; and
- - Ethical Use of Data & AI
Bio Bryan Smith is an adjunct professor in the information technology & operations management (ITOM) department as well as a data solution architect with Microsoft. He has 20 years of experience in designing, building, supporting & using analytics technologies and applies this experience...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.