Presented By O’Reilly and Intel AI
Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK

AI for managers (Day 2)

Angie Ma (ASI Data Science), Jonny Howell (ASI Data Science)
9:00–17:00 Tuesday, 9 October 2018
Location: Hilton Meeting room 3/4

What you'll learn

Explore key AI and machine learning concepts and techniques


We 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
Photo of Angie Ma

Angie Ma

ASI Data Science

Angie Ma is cofounder and COO of ASI Data Science, a London-based AI tech startup that offers data science as a service, which has completed more than 120 commercial data science projects in multiple industries and sectors and is regarded as the EMEA-based leader in data science. Angie is passionate about real-world applications of machine learning that generate business value for companies and organizations and has experience delivering complex projects from prototyping to implementation. A physicist by training, Angie was previously a researcher in nanotechnology working on developing optical detection for medical diagnostics.

Jonny Howell

ASI Data Science

Jonny Howell is an associate on ASI Data Science’s consulting team. Previously, he was an innovation consultant at Santander UK, where he led the creation and implementation of the company’s data science strategy, a central part of the COO’s digital transformation program. Jonny has worked on a variety of different data science projects across multiple industries, from engagements focused on increasing operational efficiency to identifying new business opportunities. He holds a law degree from Bristol University. In his spare time, he loves playing the guitar. In a different life, he supported the one-hit wonder Toploader.

Comments on this page are now closed.


Picture of Angie Ma
5/12/2018 9:32 GMT

Hi Jen, hope you’re well. Would be delighted to continue the conversation. Jonny (my colleague at the training) dropped you an email just after the session, and he also dropped you another email yesterday. Hope it hasn’t gone to your spam. Do let us know if you don’t receive it. Thanks. Angie

4/12/2018 10:29 GMT


I attended the course, and would like to have the email contacts of the instructors for some follow-up discussions. Please send it to me. Thank you.