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LLAIPF 2021 : Data for AI: Lessons Learned from AI Project Failures | |||||||||||
Link: https://events.cognilytica.com/CLNjA5N3wxOA | |||||||||||
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Call For Papers | |||||||||||
Featured Speakers: Kathleen Walch and Ron Schmelzer, Managing Partners and Principal Analysts at Cognilytica
Far too often, agencies, organizations, and consulting firms are running data and AI projects without taking the right steps to ensure their success. Agile and iterative approaches have become adopted best practices for application development projects, but why don’t we have something similar when it comes to advanced analytics, big data, and AI projects? Without using best-practices approaches that standardize steps for data preparation, data identification, and data protection, it’s hard to achieve the success you’re expecting, wasting money and resources, leading to failure. In this session, they'll provide an introduction to Cognitive Project Management for AI (CPMAI) methodology to provide you with the foundation needed for project success, especially as you incorporate advanced analytics and AI projects. The CPMAI methodology is the established best practice for AI & ML projects, and increasingly will be demanded by organizations and agencies that plan to develop, procure, and deliver AI and advanced analytics projects. In this session, we will provide real world examples of how CPMAI methodology allows organizations to be more successful and competitive in their AI and big data project efforts. Agenda: 11:30-12:30pm: Featured Presentation 12:30-13:00pm: Your Q&A and interaction |
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