Put AI to Work
April 15-18, 2019
New York, NY
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In-Person Training
AI for managers (SOLD OUT)

Michael Li (The Data Incubator), Russell Martin (The Data Incubator)
Monday, April 15 & Tuesday, April 16,
9:00am - 5:00pm
AI Business Summit
Location: Rendezvous
Secondary topics:  AI in the Enterprise
Average rating: **...
(2.33, 3 ratings)

Participants should plan to attend both days of this 2-day training course. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Tuesday.

Michael Li and Russ Martin offer a nontechnical overview of AI and data science. You’ll learn common techniques and how to apply them as well as common pitfalls to avoid. Along the way, you’ll pick up the language of AI and develop a framework to be able to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making.

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

  • Identify and prioritize which projects a company should pursue
  • Identify potential pitfalls in projects before they start
  • Communicate business objectives to data professionals
  • Understand the business implications of technical decisions and be able to assess the risk-reward trade-offs of different projects
  • Translate data science insights for business professionals and decision makers

This training is for you because...

  • You work with data scientists or analysts regularly.
  • You manage teams or projects with a significant data component.
  • You find yourself translating between data and management.


Introduction to AI and data science

  • Terms and definitions: What does machine learning mean?

  • Historical context and present day

  • Drivers for AI and data science

  • What’s so different about big data?

  • AI is eating the world.

  • Making AI practical

Algorithms and techniques

  • Data formats, databases, and schemas

  • Evaluating model performance and validating models

  • Terminology: Regression, classification, supervised, and unsupervised

  • Advanced models: Random forests, support vector machines, deep learning, and neural networks

Industry use cases

  • Finance

  • Healthcare

  • Industrial

  • Technology 

AI within the organization

  • Maturity levels for AI

  • Evaluating good projects for AI

  • Build versus buy and hire versus train

  • Skills, tools, and platforms needed for AI

  • Structuring data and AI initiatives within your organization: Successful and cautionary tales


Common pitfalls and fallacies in AI and data science

  • AI and data science in the headlines: The good, the bad, and the ugly

  • Legal and regulatory implications

  • Litigation and liabilities of bad data science

  • Common fallacies in data science and AI

  • Lying with statistics and how to spot it

About your instructors

Photo of Michael Li

Tianhui Michael Li is the founder and president of the Data Incubator, a data science training and placement firm. Michael bootstrapped the company and navigated it to a successful sale to the Pragmatic Institute. Previously, he headed monetization data science at Foursquare and has worked at Google, Andreessen Horowitz, JPMorgan, and D.E. Shaw. He’s a regular contributor to the Wall Street JournalTechCrunchWiredFast CompanyHarvard Business ReviewMIT Sloan Management ReviewEntrepreneurVentureBeat, TechTarget, and O’Reilly. Michael was a postdoc at Cornell, a PhD at Princeton, and a Marshall Scholar in Cambridge.

Russell Martin is a data scientist in residence at the Data Incubator, where he instructs fellows, teaches online courses, and leads training courses with corporate partners. Russ lived and worked in the UK for 17 years, including at Warwick University and the University of Liverpool, where he taught in the Department of Computer Science. He holds a PhD in applied mathematics from the Georgia Institute of Technology.

Conference registration

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

Comments on this page are now closed.


03/28/2019 8:53pm EDT

Any chance that this session will reopen with new spots?