Presented By O’Reilly and Intel AI
Put AI to Work
April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY

In-Person Training
AI for managers

Sunday, April 29 through Monday, April 30
Location: Sugar Hill at Sheraton

Participants should plan to attend both days of this 2-day training course. Platinum and Training passes do not include access to tutorials on Monday.

Richard Sargeant and Myles Kirby offer a condensed introduction to key AI and machine learning concepts and techniques, showing you what is (and isn't) possible with these exciting new tools and how they can benefit your organization.

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

  • Explore key AI and machine learning concepts and techniques

Richard Sargeant and Myles Kirby offer a condensed introduction to key AI and machine learning concepts and techniques, showing you what is (and isn’t) possible with these exciting new tools and how they can benefit your organization. You’ll learn a language and framework to talk to both technical experts and executives in order to better oversee the practical application of data science in your organization.


Introduction to AI

  • Course objectives: AI for everyone
  • Definitions: AI, machine learning (including deep learning, reinforcement learning), data analytics, customer science, etc.
  • Historical context: AI past and present
  • Present-day usage
  • AI within the corporate context
  • Significance and urgency: Why now, and why you?

AI in industry today: Practical applications and benchmark leaders

  • A selection of practical applications
  • Strategic approaches: Commissioning versus procurement (build or buy?)
  • AI maturity models and the enabling preconditions within your organization to use AI well (data, skills, tools, etc.)

Data in your organization: What are your raw materials?

  • What data assets do you have, where does it live, who owns those systems, where are the gaps, and how could you fill them (e.g., by buying data or installing sensors)?
  • What skills do you have access to from your part of the business, and what gaps might there be?
  • What tools do you use, where are the gaps, what other options are there?

Project selection: What makes a good AI use case?

  • Overview of the four key criteria for successful project selection and how to assess them
  • Group exercise: Create a project longlist (often categorized broadly within marketing, operational efficiency, operational effectiveness, and commercial optimization)
  • Scoring longlist against key criteria and plenary discussion

Managing an AI project: How is it is different from other projects?

  • Similarities and differences
  • Project lifecycle and timescales
  • Project delivery methodology
  • Typical staffing profiles
  • Cost estimates for external suppliers (for data science as a service and for consulting)
  • Performance metrics
  • Operations and maintenance
  • Governance and risk management

Leading or supporting a data transformation

  • What is data transformation (as opposed to gradual reform), and when might it be
  • necessary?
  • The ABCs of data transformation
  • Common pitfalls facing successful data transformation initiatives
  • Different operational models for data science within a modern organization
  • Next steps

About your instructors

Photo of Myles Kirby

Myles Kirby is a commercial principal at ASI. Miles has extensive experience in data and digital transformation in the private and public sectors. Over his career, he has worked with executive teams across six industries in four continents, including advising the UK government on its National Digital Transformation strategy and developing a new data strategy for a FTSE 10 oil and gas company. Previously, he was a manager at Accenture, where he cofounded the Digital Strategy practice. His policy research on innovation and entrepreneurship has been covered in international media outlets such as Wired, the Wall Street Journal, and the Financial Times.

Photo of Richard Sargeant

Richard Sargeant is the chief commercial officer at ASI. Richard has board-level experience helping senior leaders across a variety of sectors transform their businesses to use AI effectively. Previously, he was director of transformation at the Home Office, where he oversaw the creation of the second-most advanced in-house machine learning capability in the UK government, was one of the founding directors of the UK Government Digital Service, and worked at Google. He has also worked at the Prime Minister’s Strategy Unit and HM Treasury and is the non-executive board member at Exeter University with responsibility for digital, data, and technology.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package.