AI Data Strategy: Data Procurement and Storage
AI Data Strategy: Data Procurement and Storage
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 2m | 204 MB
Instructor: Lillian Pierson, P.E.
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 2m | 204 MB
Instructor: Lillian Pierson, P.E.
This course is designed for developers, machine learning engineers, data engineers, data scientists, and cloud professionals who want to master the art of developing data strategy in AI product development. Learn how to effectively source, clean, and manage both structured and unstructured data to optimize machine learning and generative AI models.
The course also covers advanced topics such as future-proofing data storage, ensuring compliance, and securing data in AI-driven environments. Through practical lessons and real-world case studies, AI product managers, tech startup founders, and technology executives can also gain valuable insights into how strategic data decisions can drive product success and innovation. Whether you’re building AI products or overseeing their deployment, this course equips you with the essential data skills to thrive in AI-intensive industries.
Learning objectives
- Describe the role of data strategy in AI product development, including how strategic data storage and procurement decisions impact the success of AI-driven solutions.
- Evaluate various data procurement and storage solutions, assessing their scalability, performance, and cost-effectiveness in the context of AI products.
- Execute best practices for ensuring data security, compliance, and future-proofing storage solutions in AI product development.
- Analyze real-world case studies to extract valuable lessons on how strategic data decisions can drive successful outcomes in AI product development.
AI Data Strategy: Data Procurement and Storage
