Learning Objectives

Intellectual Point
Administration

[36%] Focuses on administering AI infrastructure components, including Fleet Command, Slurm clusters, Base Command Manager (BCM), and configuring Multi-Instance GPU (MIG) for AI and HPC workloads.

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Installation and Deployment

[26%] Covers the installation and configuration of BCM, initializing Kubernetes on NVIDIA hosts, deploying containers from NGC and cloud VMI, understanding storage requirements, and deploying DOCA services on DPU Arm.

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Troubleshooting and Optimization

[20%] Involves using system management tools to troubleshoot issues and optimize performance across AI infrastructure components.

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Workload Management

[16%] Addresses administering Kubernetes clusters and utilizing system management tools to manage and troubleshoot AI workloads effectively.

  • The Certified AI Operations Professional Training Course at Intellectual Point is meticulously curated to equip individuals with the skills and knowledge necessary to manage and optimize AI-driven systems and applications. This course not only prepares you for the Certified AI Operations Professional certification exam but also emphasizes practical applications of AI in operational settings, focusing on integrating AI technologies and enhancing system efficiencies. Learners will engage with a comprehensive curriculum that spans both introductory and advanced AI concepts, blending theory with hands-on practice to cultivate a robust foundation for managing AI-driven infrastructures.
  • Throughout the training, you will explore topics such as AI system architecture, intelligent process automation, data management, and AI-based security solutions. The course includes interactive labs and real-world projects designed to reinforce your understanding of AI technologies and their operational impact. By the end of the program, you’ll be well-prepared to pass the certification exam and proficiently apply AI technologies to improve organizational efficiencies and drive innovation. By the end of this course, participants will:
  • 1) Effectively integrate AI technologies into existing systems to enhance operational efficiencies.
  • 2) Develop and automate intelligent processes to streamline business operations.
  • 3) Design and implement data management strategies for optimal AI performance.
  • 4) Apply AI-based security measures to safeguard operational environments.
  • 5) Gain a comprehensive understanding for the Certified AI Operations Professional certification.

Module by Module Learning Outline

Program Materials

Introduction to AI Operations

Learning Objectives

  • Understand key AI concepts and their relevance in operational settings.
  • Identify the role of AI in enhancing system efficiencies.

Topics Covered

  • Overview of AI in Operations: Definition and scope of AI operations. Benefits of integrating AI into operational systems.
  • AI Systems Architecture: Core components of AI architecture. Designing scalable AI infrastructure.

Intelligent Process Automation

Learning Objectives

  • Learn how to automate business processes using AI.
  • Analyze the impact of AI driven automation on operational workflows.

Topics Covered

  • Basics of Process Automation: Key concepts in process automation. Tools and technologies for AI-driven automation.
  • Implementing Intelligent Automation: Steps to automate processes using AI. Evaluating performance improvements through automation.

Data Management for AI Systems

Learning Objectives

  • Develop data management strategies for optimizing AI performance.
  • Implement effective data handling techniques for AI applications.

Topics Covered

  • Data Management Fundamentals: Overview of data storage and processing in AI. Techniques for efficient data management.
  • Advanced Data Strategies: Leveraging big data for AI insights. Data quality and governance in AI systems.

AI Based Security Solutions

Learning Objectives

  • Apply AI based measures to enhance system security.
  • Understand the role of AI in modern cybersecurity frameworks.

Topics Covered

  • Introduction to AI Security: Security challenges in AI systems. AI’s role in threat detection and prevention.
  • Implementing AI Security Solutions: Designing AI driven security protocols. Case studies of AI in cybersecurity.

Real World AI Applications and Deployment

Learning Objectives

  • Explore case studies of AI applications in various industries.
  • Gain skills to deploy AI solutions effectively within an organization.

Topics Covered

  • AI Applications Across Industries: Examples of AI solutions in manufacturing, healthcare, and finance. Lessons learned from successful AI deployments.
  • Deployment and Evaluation of AI Solutions: Process of deploying AI in real world settings. Techniques for evaluating AI technology performance.

Certification Exam Preparation

Learning Objectives

  • Review key concepts and areas for the Certified AI Operations Professional exam.
  • Develop strategies for successful exam completion.

Topics Covered

  • Exam Content Review: Breakdown of exam topics and weightage. Tips for prioritizing study efforts.
  • Practice Exams and Strategies: Mock exams for self-assessment. Time management and question handling techniques during the exam.

Tuition & Hours

Tuition is charged by course. The cost of the certification exam is not included in tuition and is a separate cost based on the current rates as set by the vendor.

Course Total Hours Tuition
AIML-200: Certified AI Operations Professional 72 $4,499.00

Books & Supplies

There are no additional charges for books or supplies.

Indirect Costs

Should a student wish to obtain the NVIDIA Certified Professional: AI Operations exam, the cost is an additional fee not covered in tuition. While encouraged, the exam is not a required expense to be paid at the time of enrollment. To obtain a voucher for the certification exam, you will need to purchase it separately.

Course Exam Exam Fee
AIML-200: Certified AI Operations Professional NVIDIA Certified Professional: AI Operations $400

Program Award

Upon successful completion of the course, the student will receive a Certificate of Completion for Certified AI Operations Professional Training.

* Exam fees are quoted based on time of publication. Voucher prices may change based on vendor rates and are updated accordingly. Please contact Intellectual Point to verify exam fee charges.

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AI in the Data Center an entry-level certification that validates foundational concepts of adopting artificial intelligence computing by NVIDIA in a data center environment.

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AI in the Data Center Course at Intellectual Point Includes:
  • Live instructor-led training in modern classrooms

  • Thorough review of all NIVIDIA Certified Associate – AI in the Data Center topics by industry experts

  • Hands-on labs on real NVIDIA’s GPU technologies 

  • 24 x 7 access to the real labs in classrooms and remotely

  • 100% latest material & and realistic practice questions

  • Confidence building hands-on training

  • Authorized Pearson VUE testing at the same location to help you complete your exam*

  • Study material, notes, videos, and practice questions included in the course price

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