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.

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Course feature Course detail
Dates: –
Topic: Strategy
Format: On Campus
Location:
Price:

Most companies offer tuition reimbursement for SMU programs, check with your HR department for details.

Questions?

To learn more about the program, contact us at 214.768.3335 or exed@smu.edu

Topics

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

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.

Schedule

 
8:30 a.m. – Noon

Machine Learning & AI:
Hype vs. Reality

Bryan Smith

Getting Started with Machine Learning & AI

Jeff Johnson
1:00 p.m. - 4:30 p.m.

Organizing for Machine Learning & AI

Travis Grubbs

Long-Term Implications of Machine Learning & AI

Jeff Mettel

 

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Next Steps

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