SANTA CLARA — As the world of generative AI continues to evolve, the demand for skilled professionals who can effectively manage the infrastructure required to develop and deploy AI solutions has never been higher. To address these growing needs, NVIDIA has introduced two new certifications designed for professionals working with AI infrastructure and operations.
These new professional-level certifications target network and system administrators, DevOps and MLOps engineers, and anyone involved in AI technology deployment, offering structured learning paths to help individuals develop and validate the essential skills required to work with cutting-edge AI systems.
NVIDIA’s certification program is designed to enhance the career prospects of those in the AI field, equipping them with in-depth knowledge in areas such as AI infrastructure, deep learning, and accelerated computing. The program was created in collaboration with industry experts, ensuring that the content is both practical and up to date, emphasizing real-world application in addition to theoretical principles.
The NVIDIA-Certified Professional: AI Infrastructure certification is aimed at professionals who wish to demonstrate advanced skills in deploying and optimizing AI infrastructure. Candidates will be tested on their expertise in GPU and DPU installation, hardware validation, and system optimization for both AI and high-performance computing (HPC) workloads. The exam also covers proficiency in configuring multiple-instance GPUs (MIG), deploying the NVIDIA BlueField operating system, and integrating NVIDIA’s cloud-native stack with Docker and NVIDIA NGC.
To help professionals prepare for this certification, NVIDIA recommends the AI Infrastructure Professional Workshop. This hands-on course covers critical aspects of AI data center technologies, including compute platforms, GPU operations, networking, storage solutions, and BlueField DPUs, helping participants enhance their AI infrastructure capabilities.
The NVIDIA-Certified Professional: AI Operations certification, on the other hand, focuses on professionals looking to deepen their expertise in managing AI operations. This exam tests knowledge in managing AI data centers, including Kubernetes, Slurm, MIG, BCM, NGC containers, storage configuration, and DPU services. To prepare, candidates are encouraged to attend the AI Operations Professional Workshop, which provides hands-on experience in managing AI data centers and practical experience with NVIDIA AI software solutions such as NGC containers and the NVIDIA AI Enterprise software suite.
Both certifications build upon the foundational knowledge covered in NVIDIA’s NVIDIA-Certified Associate: AI Infrastructure and Operations certification. Additional certifications available include the NVIDIA-Certified Associate: Generative AI LLMs, which validates skills in using large language models, and the NVIDIA-Certified Associate: Generative AI Multimodal, focusing on multimodal AI content creation.
One individual who has benefitted from the program is Saleh Hassan, an embedded software engineer at Two Six Technologies, who successfully completed three NVIDIA certification exams earlier this year. He said, “The knowledge I gained has definitely made me a better developer when it comes to integrating AI,” and he encourages others to pursue these certifications as a key milestone in advancing their AI careers.
NVIDIA’s certifications form part of a comprehensive learning path, providing a mix of foundational courses, advanced training, and hands-on labs to ensure candidates are thoroughly prepared for real-world applications. These certifications not only support individual career development but also help organizations enhance their workforce’s capabilities in the rapidly expanding AI field.
Explore the options on the NVIDIA Certification portal
