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Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA

In-Person Training
AI and data science for managers

Michael Li (The Data Incubator), Zachary Glassman (The Data Incubator)
9:00am-5:00pm
Tuesday, September 4 through Wednesday, September 5
Location: Continental 9
Secondary topics:  AI in the Enterprise
Average rating: ****.
(4.00, 1 rating)

Participants should plan to attend training courses on both Tuesday and Wednesday. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Wednesday.

Michael Li and Zachary Glassman offer a nontechnical overview of AI and data science. You'll learn basic concepts and vocabulary and develop a framework that will allow you 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
  • Understand 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 are a business professional who wants to learn about data and AI.

Michael Li and Zachary Glassman offer a nontechnical overview of AI and data science. You’ll learn basic concepts and vocabulary and develop a framework that will allow you to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making. Along the way, Michael and Zachary discuss common techniques and how to apply them in your organization as well as common pitfalls to avoid.

Outline

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?
  • Why 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 Journal, TechCrunch, Wired, Fast Company, Harvard Business Review, MIT Sloan Management Review, Entrepreneur, VentureBeat, TechTarget, and O’Reilly. Michael was a postdoc at Cornell, a PhD at Princeton, and a Marshall Scholar in Cambridge.

Photo of Zachary Glassman

Zachary Glassman is a data scientist in residence at the Data Incubator. Zachary has a passion for building data tools and teaching others to use Python. He studied physics and mathematics as an undergraduate at Pomona College and holds a master’s degree in atomic physics from the University of Maryland.

Conference registration

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

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Comments

Angelo Del Priore |
08/14/2018 9:58am PDT

Can you provide the schedule (i.e., rough breakdwon of time for each topic) for AI and data science for managers?