For network professionals who are looking to advance their careers and demonstrate to employers that they’ve reached another level of career-boosting and salary-lifting expertise, it could be time to consider pursuing certifications in AI and AIOps (artificial intelligence for IT operations).
The demand for AI skills is growing – along with salary expectations. As many as 92% of employers believe their IT departments will be the biggest beneficiaries of AI, and they’re willing to pay an average of 47% more for IT workers with AI skills. However, nearly three in four said that they can’t find the talent they need, according to a survey conducted by Access Partnership and Amazon Web Services.
Similarly, AI and machine learning specialists top the list of fast-growing jobs, according to the World Economic Forum’s Future of Jobs report. Organizations identified skills gaps and an inability to attract talent as the key barriers preventing industry transformation.
At the same time, enterprises believe that applying AI to IT operations will pay off by way of streamlined IT management. In new research from Enterprise Management Associates, 96% of IT organizations said they believe generative AI can make their IT personnel more productive, and 98% believe AI can be helpful for summarizing insights from IT dashboards to show user experience, describe current trends in bandwidth utilization, and determine how alerts are related.
Although it’s still early days, a number of outfits – including core enterprise IT vendors like Cisco and IBM, the Big 3 cloud service providers, and independent educational organizations – have begun to offer certifications in AIOps, AI, and machine learning. Here are some options to consider.
Cisco: CCDE-AI Infrastructure certification
At this year’s Cisco Live conference, Cisco announced a new certification: Cisco Certified Design Expert (CCDE) AI Infrastructure. This vendor-agnostic certification is for IT professionals who want to gain the expertise needed to design, provision, and optimize networks and compute power critical for today’s demanding AI workloads.
In the course, IT professionals learn skills such as designing network architectures optimized for AI workloads; GPU optimization; building for high-performance generative AI network fabrics; and ensuring the security, sustainability and compliance of networks that support AI. They also learn to incorporate the unique business requirements of AI, such as trade-offs for cost optimization and power, and the matching of computing power and cloud needs to manage carbon use.
These skills are desperately needed by technology leaders and the enterprises they support. According to the Cisco AI Readiness Index, 90% of organizations are investing to try to overcome skills gaps in AI.
The technology list for the new CCDE-AI Infrastructure certification covers four high-level domains, according to Cisco:
- AI/machine learning, compliance, and governance: This section differentiates between various AI use cases, how they impact the network, and how that network should be designed. This domain covers designing for regulations regarding data sovereignty and data locality, energy use, and cost optimization.
- Network: This domain includes the properties and functions provided by the network, the differences between different connectivity models, and ensuring adequate bandwidth.
- Security: Security must be built into the infrastructure, not bolted on later. This domain includes secure networks and the process of securing AI applications with relevant web filtering techniques. It also includes AI-enabled tools for log analysis and correlation
- Hardware and environment: This domain requires a thorough knowledge of specific hardware used to run AI, enabling candidates to choose and use them appropriately. This domain also includes storage options and the use of various AI-enabled tools for log analysis and correlation.
The CCDE v3.1 AI Infrastructure certification is so new that it won’t be available for testing until Feb. 9, 2025, coinciding with Cisco Live Amsterdam. But interested network professionals can visit CCDE Unified Exam Topics for materials to help prepare for the exam.
IBM: Cloud Pak for Watson AIOps
For network admins running IBM systems, the company is offering IBM Certified Administrator – Cloud Pak for Watson AIOps. This certification demonstrates that a system admin has expertise in IBM Cloud Pak for Watson AIOps v3.2, including AI Manager, Event Manager, and Metric Manager. The certification covers planning, sizing, installation, daily management and operation, security, performance, configuration of enhancements (including fix packs and patches), customization and/or problem determination.
During exam development, the subject matter experts define all of the tasks, knowledge, and experience that an individual would need to successfully fulfill their role with the product. The exam is 90 minutes, 65 questions, and assumes a level of on-the-job experience.
Microsoft: Azure AI Fundamentals
Microsoft is offering a certification that enables IT pros to demonstrate knowledge of machine learning and AI concepts within the Microsoft Azure environment. Data science and software engineering experience are not required, but candidates would benefit from having an awareness of basic cloud concepts and client-server applications. Azure AI Fundamentals can help to prepare candidates for other Azure role-based certifications, like Azure Data Scientist Associate or Azure AI engineer associate, but it’s not a prerequisite.
Applicants are expected to describe AI workloads and considerations, describe fundamental principles of machine learning on Azure, describe features of computer vision workloads on Azure, describe features of Natural Language Processing (NLP) workloads on Azure, and describe features of generative AI workloads on Azure. The exam costs $99 and is 45 minutes long.
AWS: Certified AI Practitioner and Certified Machine Learning Engineer
On June 11, Amazon launched a suite of new AIOps-related certifications. AWS Certified AI Practitioner is a foundation-level cert designed for IT managers to showcase their understanding of AI and generative AI concepts, ability to recognize opportunities that benefit from AI, and knowledge of using AI tools responsibly.
For training resources for AWS Certified AI Practitioner, candidates can access eight free courses, including Fundamentals of Machine Learning and Artificial Intelligence, Exploring Artificial Intelligence Use Cases, and Application and Essentials of Prompt Engineering. These courses provide real-world use cases for AI, ML, and generative AI; explain how to select a foundational model; and explore concepts and techniques involved in crafting effective prompts. The exam is two hours, 85 questions, and costs $75.
A second certification, AWS: Certified Machine Learning Engineer – Associate, is designed for IT pros with at least one year of experience building, deploying, and maintaining AI and ML workloads using AWS SageMaker, Amazon’s machine learning platform. The certification is for people who want to demonstrate their ability to make AI models available for real-time usage. The exam is 170 minutes, 85 questions, and costs $75. AWS says it will continue to roll out additional AIOps-related certifications.
Google: Professional Machine Learning Engineer
Google recently launched a certification program for network professionals running enterprise resources in the Google Cloud who want to boost their skillset. A Google Professional Machine Learning Engineer uses Google Cloud technologies to handle large, complex datasets and create repeatable, reusable code. The ML Engineer is proficient in the areas of model architecture, data and ML pipeline creation, and metrics interpretation. The ML Engineer is familiar with the foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance.
The Professional Machine Learning Engineer exam assesses the ability to architect low-code ML solutions, collaborate within and across teams to manage data and models, scale prototypes into ML models, automate and orchestrate ML pipelines, and monitor ML solutions. The two-hour text has 50-60 multiple-choice questions and costs $200.
Other AIOps training and certification opportunities
- The DevOps Institute, recently purchased by PeopleCert, offers a certification called AIOps Foundation. The course addresses key principles and foundational concepts along with core technologies of AIOps – big data and machine learning. It covers the evolution of AIOps, the difference between AIOps and IT Operations Analytics, how AIOps can be integrated into organizational frameworks, its impact on DevOps, site reliability, security, and system complexity. The course also looks at AI and machine learning in AIOps, big data, AIOps use cases, challenges and opportunities, and metrics to quantify the outcomes of implementing AIOps. The exam is 60 minutes, 40 multiple choice questions, and costs $270.
- Global Skills Development Council offers an AIOps Foundation certification for individuals seeking to validate their expertise in AI Operations (AIOps). By obtaining the GSDC AIOps certification, professionals demonstrate their proficiency in leveraging AI and automation techniques to enhance the monitoring, analysis, and management of complex IT environments. AIOps certification equips certified AIOps professionals with the necessary tools and techniques to address modern IT challenges, improve operational efficiency, and drive business value. The objectives are to understand the core principles of AIOps technology, to apply those techniques in IT operations, to proactively manage incidents, to automate and optimize IT processes, to master machine learning algorithms, and to understand the business impact of AIOps implementations. The syllabus covers data collections and standardization, anomaly detection, causal analysis, prediction and trend identification, remediation and automation, streamlining alert management, the future of AIOps and data analytics, AIOps platforms, use cases and organizational mindset, and evaluating the impact of AIOps. It is recommended that attendees have experience working in an IT-related environment and a solid understanding of IT terminology. The exam is 60 minutes, 40 multiple-choice questions, and costs $400.
- Udemy offers a course entitled AIOps Fundamentals for Beginners. This course consists of three hours of on-demand video and 10 downloadable resources that cover AIOps concepts, roadmaps, workflows, use cases, types, challenges, solutions, and best practices.
- Great Learning Academy offers a free course that covers the core principles of AIOps, including the role of AI and ML in AIOps, AIOps capabilities, and implementation. The self-paced course provides 30 minutes worth of material and provides a certificate upon completion.
- Pluralsight offers a course entitled Artifical Intelligence Essentials: AIOps. The course teaches the essentials of AIOps to help attendees assess how they can apply it to their organization. The one-hour course covers the benefits of AIOps, implications for business, use cases, key capabilities, and key dimensions of IT Ops monitoring.
- Skillsoft offers a course on AIOps and MLOps basics. The one-hour and 25-minute course provides 14 videos that cover the basics of AIOps, uses cases, implementations, tools, and best practices. The course also explains the difference between AIOps, MLOps, and DevOps.
Source:: Network World