Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

In-Person Training
Data science for managers

Angie Ma (ASI), Maria Diaz (ASI Data Science)
Monday, March 5 & Tuesday, March 6, 9:00am - 5:00pm
Strata Business Summit
Location: 212 D
Average rating: ****.
(4.00, 2 ratings)

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

Angie Ma offers a condensed introduction to key data science 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 data science and machine learning concepts and techniques

Angie Ma offers a condensed introduction to key data science 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.

Outline

Introduction to data science

  • Course objectives: AI for everyone
  • Definitions: Data science, machine learning, big data, data analytics, customer science, etc.
  • Historical context: How data science started, integration with computing, etc.
  • Present-day usage
  • Data science within the corporate context
  • Significance and urgency: Why now, and why you?

Data science in industry today: Practical applications and benchmark leaders

  • A selection of practical applications
  • Strategic approaches: Commissioning versus procurement (build or buy?)
  • Data science maturity models and the enabling preconditions within your organization to
    use data science 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 by (e.g. 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 data science project?

  • 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 a data science project: How is it different from other projects?

  • Similarities and differences
  • Project lifecycle and timescales
  • Project delivery methodology
  • Typical staffing profiles
  • Data scientist culture
  • 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 Angie Ma

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.

Maria Diaz is a Principal Consultant at ASI. She has more than ten years experience in helping organisations solve business problems by applying digital solutions and artificial intelligence. She also has expertise in advising fast growing organisations to transform their processes to achieve scale and growth. Before joining ASI, Maria was responsible for the client digital operations at Teradata Marketing Applications, leading the customer success, technical and project management teams. Prior to that, Maria managed the digital production team at eBay Enterprise.

Conference registration

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

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Comments

Picture of Steve Littlefield
Steve Littlefield |
03/01/2018 3:32am PST

Will there be any language- and/or tool-specific training as a part of this course?

Picture of Angie Ma
Angie Ma | COO
02/04/2018 6:58pm PST

@Tal Zohar: thanks for reaching out. I believe both Platinum and Training passes give you access to the training course. Tutorials are different which are not included in those two types of passes. Hope this helps.

Tal Zohar | HEAD OF BUSINESS ANALYSIS
02/03/2018 10:45pm PST

Hi
Which ticket should I buy in order to attend the Data science for managers training?
it says below the picture that:
Participants should plan to attend both days of this 2-day training course. Platinum and Training passes do not include access to tutorials on Tuesday.
So which tickets DOES allow an entrance to this training?