Episode 1 of 15
Full video series click https://aka.ms/AI-300onYouTube
This video brings together the full picture of how machine learning solutions are designed for real-world success—from ingesting and serving data, to choosing the right development environment and compute resources, and finally integrating trained models into applications. You’ll learn how thoughtful architectural choices made early in the process enable scalability and efficiency, how different Azure services support experimentation and production workloads, and how deployment through endpoints turns models into consumable services. Together, these concepts demonstrate that building effective ML solutions isn’t just about training models—it’s about designing end-to-end workflows that are scalable, maintainable, and ready to deliver business value.
Immerse in rich interactive materials with self-directed learning https://aka.ms/AI-300onLearn
00:00 Video Start
01:06 Course overview
07:28 Course materials
08:17 Microsoft Certification exam
09:16 Operationalize machine learning and generative AI solutions
46:10 Knowledge Check
46:48 Summary
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