Strategic Data Collection, Modeling, and Quality Management for AI Systems

Strategic Data Collection, Modeling, and Quality Management for AI Systems
Released: 4/1/2025
Duration: 51m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 83 MB

In this course, data strategist Joe Squire introduces the foundational principles of strategic data collection, modeling, and quality management essential for building effective AI systems. Learn how to design a data collection strategy that aligns with business goals, focusing on the quality, relevance, and representativeness of data to support reliable AI insights. Discover ways to maintain data accuracy, identify and mitigate biases, and implement quality control practices to enhance data integrity across AI workflows. Additionally, explore data modeling basics to support AI applications, building a strong foundation for further topics in scalable storage, secure data management, and advanced AI processing techniques. By the end of this course, you will be equipped with actionable strategies to ensure high-quality data that drives accurate and unbiased AI outcomes.
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