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.
Introduction to data science
Data science in industry today: Practical applications and benchmark leaders
Data in your organization: What are your raw materials?
Project selection: What makes a good data science project?
Managing a data science project: How is it different from other projects?
Leading or supporting a data transformation
Angie Ma is cofounder and COO of Faculty, a London-based AI tech startup that provides strategy, software, and skills. Faculty has delivered more than 300 commercial data science projects across 23 sectors and 8 countries. 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.
Get the Platinum pass or the Training pass to add this course to your package.
Comments on this page are now closed.
©2018, O'Reilly Media, Inc. • (800) 889-8969 or (707) 827-7019 • Monday-Friday 7:30am-5pm PT • All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners. • firstname.lastname@example.org