It has been said before, but I’ll say it again just in case you have been living under a rock for the past couple of years: AI is everywhere.
While there is quite a variance in what AI will provide for everyone, for those in technology, there is no escape—you must be able to understand it.
For those of us in the networking world, that demand doesn’t just stop at understanding it; it’s about knowing how to build the supporting infrastructure, operationalize the technology to ensure it performs exactly as intended, and use it as a diagnostic assistant to speed time to remediation.
(Let’s be honest, though, it’s probably innocent; it’s never the network.)
If you feel that you’re behind the curve in doing all that or just need a quick refresher with the added bonus of some sweet Cisco Continuing Education (CE) credits—15 total available this time— you’re in luck.
Rev Up to Recert: Stack
Rev Up to Recert: Stack is all about AI, from both infrastructure and operational perspectives.
Let’s dive into the details as any network engineer would—starting at the lower layers and working our way up. Read on to learn more about each Learning Path, and enjoy free access from Monday, August 24, through Thursday, October 8, 2026.
Designing Cisco UCS-X Series for AI | DCUCSX
9 CE credits, 9h 21m
The Designing Cisco UCS-X Series for AI (DCUCSX) Learning Path has it all: from understanding the architecture and how the UCS-X is managed, to understanding the role GPUs play and how to size the GPU requirements based on workload, all the way to operationalizing the UCS chassis and automating deployments, configuration, storage, and networking.
For those familiar with the older 5108 UCS chassis system, the introduction will seem very familiar, as it provides a high-level overview of the UCS fabric interconnects, how the UCS chassis connects to networking and storage, and how the device is managed overall.
From there, the Learning Path moves towards understanding GPU options and effectively sizing the number of GPUs for the expected workloads.
Without this—and the ability to size the GPUs accordingly—any AI experience will be suboptimal.
The back half of the DCUCSX Learning Path focuses on operationalizing the UCS-X.
First, it kicks off with a section on deploying UCS-X with Intersight Managed Mode (IMM) and the platform’s shift to a cloud-managed model. Not only is there a lecture, but you get to deploy the chassis in IMM with a hands-on lab.
It then enables effective monitoring of the UCS-X chassis without relying on typical observability tools such as syslog and SNMP and supports operations such as firmware upgrades and the use of the hardware compatibility list (HCL).
No learning would be complete without a lab, and this course has one.
Finally, the path wraps up by using Cisco Intersight Automation (formerly Cisco Intersight Cloud Orchestrator) to build tasks, templates, and workflows that provision network, storage, and compute resources without tedious click-ops.
Again, labs are there to help you learn how to do these functions in practice.
With all of this, you’ll feel confident deploying UCS-X in your environment to support AI and non-AI (do those even exist anymore?) workloads. After spending nine and a half hours digging into this platform, you’ll not only be aware of what is possible, but you’ll also walk away with 9 CE credits.
Cisco Splunk AI Operations | CAIOP
6 CE credits, 7h 53m
OK, the infrastructure is up, and you’re monitoring all of your devices—but how do you make sense of all the logging and telemetry data coming into your logging source of truth?
Sure, there are a lot of complex regular expressions, filtering, building custom dashboards, and basically brute-forcing the data until you get it to tell you what’s going on, but there is a smarter (and more efficient) way to do all of this. It involves Splunk (a natural fit) and AI (hey, crunching data and finding patterns is something it’s really good at).
The Cisco Splunk AI Operations (CAIOP) Learning Path will help you understand how this is all possible, using the AI capabilities within the Splunk platform.
The CAIOP Learning Path consists of nearly eight hours of Splunk education and can be valuable even if you’re not an experienced Splunk practitioner or AIOps expert. It begins with a primer on AIOps and how to configure and navigate a few key areas of the Splunk interface.
Interactive activities are spread throughout these sections, so even if you don’t have access to a Splunk instance, you still get the full experience.
The next several sections build on the AIOps fundamentals and discuss how to think about incoming data, how to preprocess and normalize it, and how to build the governance and business frameworks that allow you to begin using AIOps with your business data.
The following section takes that one step further, with explanations and exercises on how to use Splunk’s Machine Learning Toolkit (MLTK). Interactive activities are spread throughout these sections to ensure that your learning is complemented by hands-on practice, cementing the concepts through kinesthetic learning.
Finally, the Learning Path concludes with how to turn what you’ve created into something the business can use; how to operationalize, integrate, and scale AIOps within an enterprise; and trends and future-looking guidance on what could be coming in the world of AIOps. This section really gets to the heart of any new technology: it’s not useful unless everyone in an organization can use it, which requires planning and consideration of myriad details.
These sections shouldn’t be skipped or glossed over—they can make or break any AIOps implementation.
Bringing it all together
Like I’ve said, there’s no escaping the prevalence of AI in today’s world.
However, through these two Learning Paths, you should feel more confident not just in using AI chatbots, but also in building the compute infrastructure to support physical AI infrastructure as well as using a data analysis platform’s included AIOps toolkit to manage large amounts of ingested data.
That means you can work smarter, not harder.
While I say they are both valuable, you can also choose one or the other, based on your job role/function or where you want your career to take you.
Learning, training, and even certifications are not a linear journey, and we specifically chose this set of Learning Paths for this Rev Up to ensure you have the choice of where you want to go.
As always, happy learning—and if you have any questions, comments, or just want to talk AI infrastructure or Splunk, find me on X (@qsnyder) or leave a comment on this blog below.
Rev Up to Recert: Stack
Earn up to 15 CE credits—free—available now through October 8, 2026.
Designing Cisco UCS-X Series for AI | Cisco Splunk AI Operations
