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NVIDIA Certified Associate: AI Infrastructure and Operations Certification Training Course

Course Overview

The NVIDIA Certified Associate AI Infrastructure and Operations Certification Training Course with Accumentum provides a comprehensive introduction to artificial intelligence (AI), machine learning (ML), and generative AI concepts, specifically tailored for NVIDIA’s infrastructure and operations. Designed for individuals managing or working with AI technologies, such as business analysts, IT managers, and sales professionals, this foundational course covers fundamental AI concepts, practical use cases, and ethical implementation using NVIDIA’s tools like RAPIDS and DGX systems. Participants will explore the NVIDIA AI ecosystem, learning to identify opportunities for AI applications, understand design considerations for foundation models, and the importance of responsible AI practices. The course also includes modules on security, compliance, and governance, preparing learners for the NVIDIA Certified Associate AI Infrastructure and Operations certification exam, equipping them with the knowledge to leverage AI for business innovation and understanding its strategic impact on organizational strategies.

Course Objectives

  • Gain knowledge of NVIDIA’s hardware and software solutions for AI, including GPUs, DGX systems, and software frameworks like CUDA and RAPIDS, to effectively support AI operations.
  • Learn to deploy, manage, and maintain AI infrastructure, ensuring optimal performance and scalability of AI applications within an NVIDIA-supported environment.
  • Focus on the ethical considerations of AI deployment, understanding how to use NVIDIA tools to ensure fairness, transparency, and accountability in AI solutions.
  • Equip participants with the skills and knowledge necessary to pass the NVIDIA Certified Associate: AI Infrastructure and Operations exam, covering topics from AI infrastructure setup to compliance and security in AI operations.

Who Should Attend

  • Individuals responsible for managing and maintaining AI infrastructure who need to understand how to integrate and optimize NVIDIA’s technology stack.
  • Those involved in the operational aspects of data centers looking to specialize in deploying and managing AI solutions using NVIDIA hardware.
  • Sales professionals and architects who wish to expand their knowledge of NVIDIA’s AI offerings to better serve customers and design solutions.
  • Professionals involved in AI project management or business analysis who need to grasp the operational side of AI to drive strategic decisions and implementations.

Prerequisites

  • Basic Understanding of AI Concepts: Familiarity with fundamental AI and machine learning concepts, terminology, and their applications.
  • General IT Knowledge: A foundational understanding of IT infrastructure, including networking, storage, and server management.
  • Experience with Linux Systems: Practical experience with Linux environments, as NVIDIA tools often rely on Linux-based systems for deployment and operation.
  • Familiarity with NVIDIA Hardware and Software: Basic knowledge of NVIDIA’s products like GPUs, DGX systems, and software platforms such as CUDA or NVIDIA NGC would be advantageous.

Course Content

Introduction to NVIDIA's AI Ecosystem
  • Overview of NVIDIA’s role in AI.
  • Key NVIDIA products for AI (GPUs, DGX systems).
  • NVIDIA software stack overview (CUDA, RAPIDS).
  • Integration of NVIDIA technologies in AI workflows.
Fundamentals of AI and Machine Learning
  • Basic concepts of AI, ML, and deep learning.
  • Types of learning: supervised, unsupervised, reinforcement.
  • Common algorithms and their use cases.
  • Ethical considerations in AI development.
NVIDIA Hardware for AI
  • Detailed exploration of NVIDIA GPUs for AI.
  • Architecture of DGX systems for AI workloads.
  • Performance metrics and optimization techniques.
  • Cooling and power management for AI hardware.
NVIDIA Software Tools
  • Introduction to CUDA for parallel computing.
  • Utilizing RAPIDS for data science and analytics.
  • NVIDIA NGC for AI model deployment.
  • TensorRT for optimizing AI inference.
AI Infrastructure Design and Deployment
  • Architecting AI infrastructure with NVIDIA hardware.
  • Best practices for setting up AI environments.
  • Scalability considerations for AI workloads.
  • Network design for AI data flow.
Data Management for AI
  • Data ingestion and preprocessing with NVIDIA tools.
  • Storage solutions for large datasets in AI.
  • Data versioning and lifecycle management.
  • Security and compliance in data handling.
Operational Management of AI Systems
  • Monitoring and managing AI workloads.
  • Resource allocation and load balancing.
  • Troubleshooting common AI infrastructure issues.
  • Updating and maintaining AI systems.
AI Security and Compliance
  • Security considerations specific to AI implementations.
  • Compliance with data protection regulations.
  • Implementing secure AI environments with NVIDIA tech.
  • Incident response in AI operations.
Performance Optimization
  • Techniques for optimizing AI model performance.
  • Profiling and tuning AI workloads on NVIDIA hardware.
  • Benchmarking AI systems for efficiency.
  • Energy efficiency in AI operations.
Future Trends and NVIDIA's Vision for AI
  • Emerging trends in AI technology.
  • NVIDIA’s roadmap for AI advancements.
  • Integration of AI with other technologies (IoT, edge computing).
  • Preparing for future AI infrastructure challenges.

Course Features

Interactive Learning

Engage with expert instructors and peers through training sessions, discussions, and practical exercises.

Comprehensive Study Materials

Access extensive resources, including e-books, video lectures, and practice exams.

Real-World Applications

Work on real-life case studies and scenarios to apply NVIDIA AI and ML concepts.

Certification Preparation

Receive guidance and tips to successfully pass the NVIDIA Certified Associate AI Infrastructure and Operations Certification exam.

Certification Exam

Upon completing the NVIDIA Certified Associate AI Infrastructure and Operations Certification Training Course with Accumentum, you will be thoroughly prepared to take the NVIDIA Certified Associate AI Infrastructure and Operations exam. This certification validates your foundational knowledge of AI concepts, NVIDIA's AI infrastructure, and operational practices, demonstrating your capability to identify AI opportunities, apply ethical AI practices, and effectively utilize NVIDIA's tools for AI deployment and management. Achieving the NVIDIA Certified Associate certification will notably enhance your career path, positioning you for roles that demand strategic insight into AI infrastructure and leadership in harnessing NVIDIA technologies for AI operations.

Enrollment

Enroll in the NVIDIA Certified Associate AI Infrastructure and Operations Certification Training Course with Accumentum to elevate your AI knowledge to a foundational level and earn a respected credential. This course is your pathway to becoming a certified AI infrastructure and operations associate on NVIDIA platforms. For detailed information and to secure your spot, visit Accumentum's registration page linked below.

Registration

Accumentum® LLC

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Suite 700

Arlington VA 22209

Copyright 2024 – Accumentum® LLC

All Rights Reserved. The certification names are trademarks of their owners.

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