With the rapid advancements in artificial intelligence (AI) and the increasing complexity of networks, we face a pressing need for professionals who can leverage AI to enhance network performance and security. Cisco gets it and has answered the call to equip professionals with the skills they need to design and architect AI-integrated networks.

This past week at Cisco Live, we announced our new CCDE – AI Infrastructure program. This new part of our well-known CCDE expert-level design certification focuses on optimizing for GPU utilization and low latency, complying with standards around data and privacy, and ensuring sustainable designs (given the high-power demands of AI data centers).

These initiatives are crucial now more than ever. This program complements recent additions to the CCNA and CCIE Data Center certifications, both of which include relevant Generative AI skills. By investing in AI education and certifications, Cisco is going beyond the buzz of AI — we are helping to build a workforce that is ready to meet the challenges of the future.

What’s also unique about this program is that we will provide entry-to-expert training. Ahead of the first day to test for the exam in February 2025, Cisco Learning & Certifications will provide a comprehensive AI training program.

We are starting with the following foundational-level AI courses:

So, what does this mean for you — the engineer, the developer, the network architect?

Simply put, AI will change the way you design, manage, and optimize networks, just as automation once did. At the core of this transformation is AI’s ability to process vast amounts of data and extract meaningful insights that can improve network performance, security, and reliability. And for those of you who learned Python and made your first API calls five years ago (when automation was top of mind), you can handle this AI revolution in a similar way: education.

The key is to learn how Generative AI and AI with Machine Learning (AI/ML) are pivotal in this transformation. For example, Generative AI can create new data samples, which can help simulate network scenarios, predict potential issues, and generate automated solutions, while AI/ML algorithms can analyze network data to identify patterns, detect anomalies, and make predictive adjustments. And as networks become more complex and intelligent, the need becomes critical for skilled IT professionals who can develop, deploy, and manage these AI solutions.

That’s what’s beyond the buzz; it’s not that networks will suddenly become Borg-ified and tasks somehow assimilated; it’s that using AI in and on networks mimics how we use automation. It’s a critical skill that will only grow in importance.

AI initiatives in education and certifications from Cisco

Cisco has been working in the AI space for years. You see it in our collaboration technologies and in our observability/monitoring software. ThousandEyes, for example, has been supplying data and insights for Predictive AI actions (learn more through the recently released ENNA Network Assurance Learning Path). However, the real change lately has been around Generative AI, with the accessibility of ChatGPT having introduced new experimentation and ideation around how GenAI can change the network.

Cisco Learning & Certifications has been at the forefront of integrating AI into its education and certification programs. Our initiatives are designed to ensure that networking professionals are equipped with the latest skills and knowledge to navigate the AI-driven landscape. Recently, we launched the following free tutorials you can take now to establish a foothold:

Cisco’s in-depth training on Data Science and Machine Learning for network optimization

In the rush to learn about GenAI, it’s easy to miss the importance of Predictive AI and AI/ML. Cisco’s training programs on data science and machine learning for network optimization are designed to provide professionals with a deep understanding of how to use data and AI to improve network performance. These programs cover a range of topics, including data collection and analysis, ML algorithms, and their applications in network optimization.

Check them out here:

One of the standout features of these training programs is their focus on practical, hands-on learning. This approach ensures learners are not only familiar with the theoretical aspects of AI and ML but also have the practical skills needed to implement these technologies in their networks.

The future of AI in Cisco networking technology

Look, the buzz is hot for AI. But that’s because the potential here is so great. It’s so similar to the buzz around automation (which, by the way, is still important to learn). AI and Automation are the tools of the network future. The future of AI in Cisco networking technology is incredibly promising, and you can all be authors of it. As AI continues to evolve, we can expect to see AI-driven networks becoming more autonomous and capable of self-healing and self-optimizing in real time. But that high-tech future needs a human touch to build, guide, and maintain the development. Just as with Automation, AI enhances our work and scales our abilities to allow humans to do what humans do best: create.

Time flies. When I joined the Cisco DevNet team six years ago, I was helping network engineers learn developer skills to use the power of software in the network. But now, we need to embrace the fact that practical uses of AI are here to stay. And for those I helped achieve your first “Hello, World!,” I ask you to join us in saying “Hi AI!”

I’m excited about the possibilities AI offers; but I’m more excited about how we at Cisco will enable you to build more, do more, and achieve more. I can’t wait to see the future we write together.

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Ryan Rose

Director of Product Management for Skills & Certifications

Cisco Learning & Certifications