Key Takeaways: What's New with NVIDIA Certification
Executive Summary
The NVIDIA Certification webinar provided a comprehensive overview of the certification program, aimed at validating AI skills and preparing individuals for the workforce. The session covered housekeeping tips, introduced speakers from NVIDIA, Deloitte, Computer Center, and the University of Toronto, and detailed the certification tracks and tiers. Key topics included AI infrastructure and applications, developer certifications, and the candidate experience, emphasizing global availability, remote proctoring, and immediate results. The webinar highlighted the value of certifications for career advancement, customer assurance, and enterprise team upskilling. Specific exams discussed included Generative AI, Accelerated Data Science, AI Infrastructure and Operations, and AI Networking. NVIDIA offers free study guides, recommended courses, and practice exams, with certifications accessible worldwide in multiple languages. The cost of exams varies, with discounts available, including a promotional code for 50% off until July 3rd, 2025.
Speakers
- Marco Alves, Certification Program Lead, NVIDIA
- Aeshah Hadges, Certification Manager, NVIDIA
- Gary Fluitt, Technical Certification Manager, NVIDIA
- Amlan Madhab Panigrahi, Senior AI Specialist, Deloitte
- Marc Huppert, Principal Architect/Consultant, Computacenter
- Ernest Namdar, NVIDIA Training Ambassador, Ph.D Candidate, University of Toronto
Key Takeaways
1. NVIDIA Certification Tracks: NVIDIA offers two main certification tracks: AI infrastructure and AI applications and workloads, with roles such as data center technicians, networking engineers, and developers.
2. AI Skills Validation: The certification program aims to validate AI skills, facilitate recruitment, and prepare students for the workforce, with two tiers: Associate (entry-level) and Professional (advanced).
3. Global Certification Availability: Certifications are globally available, can be taken remotely, and provide immediate results, digital badges, and certificates from Credly.
4. Developer Certification Options: Developer certifications include Generative AI LLM, Generative AI Multimodal, and Accelerated Data Science, with recommended training and free study guides.
5. AI Infrastructure Knowledge: AI infrastructure certifications cover core AI knowledge, infrastructure, and operations, suitable for data center technicians, IT professionals, and system administrators.
6. Respected NVIDIA Certifications: NVIDIA certifications are respected in the industry, accessible worldwide, and frequently updated to reflect the latest advancements in AI and GPU technologies, with discounts and promotions available.
Key Quote
Certification programs enable companies and enterprises in particular, to upskill their workforce for AI. It's also a recruiting facilitator, allowing for hiring managers to best identify the candidates that they want to consider for open positions.
Related Content
Explore Related Content.
Webinar
Watch Full Webinar here.
Maximize Your AI Career with NVIDIA Certification Programs
Certifications have become essential in today's competitive job market, especially in the AI and tech sectors. They provide a standardized measure of skills and knowledge that employers trust when evaluating candidates. For professionals looking to advance in AI infrastructure and applications, certifications from NVIDIA can be a game-changer. These certifications not only validate expertise but also open doors to better career opportunities in this rapidly growing field. NVIDIA's structured certification programs cater to various levels of expertise, allowing individuals to demonstrate their proficiency in AI infrastructure, operations, and networking. By obtaining these certifications, professionals can significantly enhance their career prospects and stay ahead in the evolving tech landscape.
NVIDIA AI Certification Tracks and Benefits
NVIDIA's certification program is designed to support various roles within the AI ecosystem through two main tracks: AI infrastructure and AI applications and workloads. The AI infrastructure track is intended for individuals in data centers, networking, DevOps, and ML Ops, focusing on the technical aspects of setting up and maintaining AI systems. The AI applications track targets developers, data scientists, and software engineers, emphasizing skills in generative AI and accelerated data science. Each track offers two tiers of certification, Associate and Professional, allowing candidates to select the level that aligns with their experience and career goals.
The certification process is straightforward and accessible globally, with exams proctored remotely. Candidates can register for exams via NVIDIA's certification webpage, which provides detailed information about each certification, including prerequisites, exam blueprints, and recommended training. Although training is not mandatory, it is highly recommended for those new to the subject matter. NVIDIA offers free study guides for each exam, which are invaluable resources for preparation, providing insights into the topics covered and recommended readings.
For enterprise teams, certifications are a strategic investment. Managers certify their teams to ensure they have the necessary skills to handle complex AI projects efficiently. Certifications from NVIDIA are particularly valuable as they validate proficiency in using GPU-accelerated tools and libraries, essential for modern AI workflows. Having certified professionals enhances team credibility and can influence client decisions when selecting a service provider. The digital badges awarded upon certification can be shared on professional networks like LinkedIn, facilitating recruiters in identifying qualified candidates.
AI Infrastructure and Networking Certifications Overview
The infrastructure professional exam targets individuals with a few years of experience in setting up data centers for AI architecture and workloads. This certification encompasses four key areas: physical layer management, system and server management, networking, and troubleshooting. The physical layer management section includes configuring and managing Bluefield, networking platforms, configuring MIG, and installing essential components for an AI data center. The system and server section involves hardware and software setup and validation. Networking covers AI topologies, while troubleshooting focuses on optimizing and identifying faults in hardware systems and GPUs.
For those who inherit and operate these systems, the operations exam is an appropriate certification. This professional-level exam also has four sections: administration, installation and deployment, configuration, and troubleshooting. The administration section includes fleet management, SLURM, and Run AI, while installation and deployment cover base command manager, cloud VMI, and Kubernetes deployment. This exam is known for its difficulty, reflecting the complexity and critical nature of tasks involved in AI operations.
Networking professionals can benefit from the updated networking exam, which now includes Spectrum X. This certification comprises three sections: AI networking architecture, Spectrum X through Ethernet, and InfiniBand. Each section covers security, configuration, optimization, and troubleshooting. The study guide provides detailed information and additional readings to aid candidates in their preparation.
NVIDIA certifications are highly esteemed in the industry, offering a competitive edge in hiring scenarios. They validate your skills and knowledge, demonstrating your initiative and alignment with industry-leading practices. Whether you are a student, early career professional, or seasoned expert, these certifications can strengthen your technical foundations and enhance your credibility in the AI field.
NVIDIA's certification program offers a robust framework for validating AI skills across various roles and levels of expertise. Whether you are an infrastructure specialist or a developer, these certifications can significantly boost your career by demonstrating your commitment to continuous learning and proficiency in cutting-edge AI technologies. By investing in these certifications, both individuals and enterprises can stay ahead in the rapidly evolving AI landscape, ensuring they are equipped to tackle the challenges and opportunities that lie ahead.
Obtaining NVIDIA certifications can be a strategic move for anyone looking to advance their career in AI infrastructure, operations, and networking. These certifications are designed to be accessible and respected, providing a benchmark for credibility in the rapidly evolving AI landscape. By preparing thoroughly and leveraging the available study guides and courses, you can position yourself as a knowledgeable and skilled professional, ready to tackle the challenges and opportunities in AI.