Data Planning, Strategy, and Compliance for AI Initiatives
Data Planning, Strategy, and Compliance for AI Initiatives
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 53m | 351 MB
Instructor: Dan Sullivan
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 53m | 351 MB
Instructor: Dan Sullivan
Dive into AI strategies that propel organizational goals with expert guidance from cloud architect, author, and Google Cloud expert Dan Sullivan. Learn how to align AI technologies with business objectives. Discover best practices for sourcing data, ensuring data quality, and preserving privacy. Gain insights into structured, semi-structured, and unstructured data, through topics such as batch and stream processing, data governance, audit trails, and ethical frameworks in AI initiatives.
Enhance your knowledge in crucial areas such as data integration, regulatory compliance, and feature engineering. Equip yourself with the skills to analyze real-world data challenges and optimize your organization's AI infrastructure. Whether you are tasked with transforming business processes or advancing AI capabilities, this course offers tools that can help you navigate complex data environments and achieve scalable, reliable AI solutions.
Learning objectives
- Plan and implement data collection and data quality assessment operations for an AI initiative.
- Plan and implement data preparation operations for AI initiatives.
- Understand the components of AI processing infrastructure and various ways to optimize that infrastructure.
- Know how to assess security considerations and apply security controls to protect the confidentiality, integrity, and availability of data and AI models.
Data Planning, Strategy, and Compliance for AI Initiatives
