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Machine Learning in Practice

A Course for Business Leaders Implementing ML in the Real World

Robbie Allen
James Kotecki

The hype around machine learning has reached epic levels, and many executives are eager to reap the benefits for their company.

This training will help managers and business executives understand and deploy machine learning in the enterprise. The training is aimed not at those doing the technical implementation, but those tasked with managing and overseeing the project, and ensuring it actually achieves business goals.

What you'll learn-and how you can apply it

  • Attendees will learn to conceptualize, evaluate, and implement machine learning solutions from a business (non-technical) perspective.
  • They will learn about the practical realities of running a machine learning project and common pitfalls to avoid.
  • Overall, this training provides the foundational business concepts they need to succeed with ML.

This training course is for you because...

You're an executive, manager, and project manager that is interested in deploying machine learning inside a company.

Prerequisites

  • Basic understanding of machine learning’s potential in their organization, although they need not be currently implementing it.

Recommended Preparation:

About your instructor

  • Robbie Allen is the CEO of Infinia ML, which helps enterprise organizations implement machine learning solutions. Previously, he founded and led Automated Insights, whose natural language generation software helped automate content production for The Associated Press, Yahoo!, and many others. Automated Insights was successfully acquired by Vista Equity Partners in 2015.

    Robbie has authored or coauthored 8 software books and has spoken at a variety of conferences including the O’Reilly AI Conference, Strata, SXSW, and the MIT Sloan CIO Symposium. He holds two Master’s degrees from MIT and is completing his Ph.D. in computer science at the UNC-Chapel Hill.

  • James Kotecki is Director of Marketing & Communications at Infinia ML. He is the former Head of Communications for Automated Insights, where he translated concepts of natural language generation for a global audience. He later started his own firm to help technology marketers tell customer stories. As a professional content creator for over a decade, he’s worked with brands including YouTube, Politico, Business Insider, LinkedIn, and DHL. He’s spoken about customer storytelling from North Carolina to South Korea, and you can see his on-camera interviews with leading executives every year at the CES electronics trade show.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

The Business Impact of Machine Learning (15 minutes)

  • Machine learning is only worthwhile if it solves a real business challenge. This section explores the most common business benefits at a high level: reducing costs, increasing efficiency, and achieving breakthroughs.

The Business Challenges of Machine Learning (15 minutes)

  • Machine learning’s promise is bright – but don’t be blinded by the hype. This section takes a clear-eyed view of ML’s limits, the ML talent shortage, interpretability issues, and more.

It All Starts with Data (15 minutes)

  • More than experts, more than algorithms, data is the sine qua non of machine learning projects. To succeed, you have to get this part right. Robbie will explain why many don’t.

Insight from the Field (5 minutes)

  • Robbie Allen delivers a unique insight earned from the trenches of machine learning services.

Q&A/Break (10 minutes)

Evaluating Machine Learning Opportunities (15 minutes)

  • When companies understand the true potential of ML, they may think of dozens of ways to apply it. But how do you know what projects are worth doing first?

Staffing and Project Planning (30 minutes)

  • Understand exactly who you need on your ML team – and the steps they need to take to succeed.

Insight from the Field (5 minutes)

Robbie Allen delivers a unique insight earned from the trenches of machine learning services.

Q&A/Break (10 minutes)

Addressing Workforce Concerns (15 minutes)

  • Bringing more machine learning and automation to your company could frighten your employees – or make them extremely happy. It all depends on the choices you make, and how you message them.

Building a Data-Centered Organization (15 minutes)

  • Exploring what it takes to embed machine learning and data science into your company’s processes and culture.

Being Prepared for the Future (15 minutes)

  • Machine learning can help businesses do amazing things today. It will help businesses do impossible things tomorrow. This section combines cutting-edge research with imagination to take a glimpse just over the horizon.

Final Q&A (15 minutes)