Platform engineering is the key to unlocking AI at enterprise scale. This course teaches you to supercharge your entire SDLC with AI-native capabilities, like automating and streamlining everything from initial builds to complex ops and compliance. Finally, you’ll learn to architect "platforms for AI," future-proofing your skill set for the next era of platform engineering.
60% report salary growth or promotion within 6 months after getting certified
Platform engineering now enables enterprise AI. This course teaches you to apply AI-native capabilities to supercharge the SDLC, streamlining everything from builds to complex operations and compliance. You will also learn to design “platforms for AI” infrastructure, preparing you for the next evolution of the platform engineering role. The course is delivered instructor-led, live, and on-demand, offering flexibility while maintaining deep, interactive learning.
Key Takeaways: Learn how to define and deliver an MVP tailored to your organization’s needs, prioritize features, and align outcomes with stakeholders.
Key Takeaways: Understand how platform engineering is evolving into AI-native systems that balance automation, governance, and trust.
Key Takeaways: Learn how AI acts as both an interface and an embedded capability to transform internal developer platforms.
Key Takeaways: Move beyond AI-assisted coding into orchestrated, agent-driven development workflows.
Key Takeaways: Design delivery systems that are predictive, adaptive, and capable of self-healing.
Key Takeaways: Transition operations from reactive monitoring to AI-driven, continuously governed systems.
Key Takeaways: Design infrastructure that meets the performance, scalability, and cost demands of AI workloads.
Key Takeaways: Build compliant, cost-aware AI platforms with strong governance and operational visibility.
Key Takeaways: Redefine the platform engineering role for an AI-native future focused on orchestration, measurement, and ethical oversight.
