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Sauder School of Business

Machine Learning: Strategic Applications

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Next dates

May 10
Vancouver, British Columbia, Canada
CAD 995 ≈USD 737
CAD 995 per day

Description

Explore Opportunities for Data-Driven Solutions in Your Organization

Machine Learning—it’s not just a buzzword any more.

A subset of artificial intelligence, Machine Learning (ML) is the science of getting computers to uncover key connections and make decisions without being explicitly programmed. It has given us many striking new applications, like self-driving cars and speech recognition.

This course introduces the tools, techniques, opportunities and applications of ML from a strategic perspective. Unlock the opportunities of this powerful technology to create greater value and competitive edge in your business.

Takeaways

  • See how ML can lead to improved performance, productivity and process effectiveness
  • Explore how ML connects data with strategic objectives for better decision making
  • Gain familiarity with ML tools and techniques
  • Get technology to do the heavy lifting in devising data-driven solutions
  • Investigate new ways to manage, lead and drive innovation
  • Harness relevant ML strategies for organizational success

Course Content

  • What is ML and how is it transforming business?
  • Key ML concepts and commonly used tools
  • ML types and best practices: examples drawn from various industries in North America, Europe and China
  • When should companies use ML vs. more traditional data-driven models?
  • Connecting strategic objectives with ML processes
  • Strategic and tactical approaches for using ML effectively in fast-changing markets
  • Types and sources of data to collect, and the tools needed to access, organize and manage it
  • Evaluating ML performance

Special Features

This course surveys ML practices being used by leading organizations across the world. It also includes an interactive session that demonstrates the tools and techniques of ML in action.

Who should attend

This workshop is for business leaders with little background in Machine Learning but who wish to identify the opportunities it offers. For example:

  • Heads of strategy and innovation
  • Executives and senior managers working in strategic, managerial or operational functions
  • Key decision makers and other business professionals looking to integrate ML into their organization

Experts

Research Interests Supply Chain Management Applied Game theory Inventory Management Selected Recent Publications "Stable Supplier Coalitions in Assembly Systems with Commodity Components". Co-authors: G. Sosic and C. Tong. Forthcoming in Operations Research. "Patient Prioritization in Eme...

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