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NCA-AIIO: NCA - AI Infrastructure and Operations Certification Video Training Course

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  • 94 Students Enrolled
  • 72 Lectures
  • 4 Hours
  • 5.0 Rating
$27.49
$24.99

Curriculum For This Course

  • Introduction

    Video Name Time
    1. Introduction 1:28

  • Certification Details

    Video Name Time
    1. Certification Details 2:31
    2. Topics Covered in Certification 1:57

  • Module 1 - Fundamentals

    Video Name Time
    1. Drivers of AI evolution 2:19
    2. AI use cases across industries 1:59
    3. AI, ML, DL, Gen AI 3:14
    4. Analogy for AI, ML, DL, Gen AI 3:14
    5. Transformer Model 4:49

  • Module 2 - Inside an AI centric Data Center

    Video Name Time
    1. Inside an AI centric Data Center 4:02
    2. Power Usage Effectiveness (PUE) 5:01
    3. The Compute Power 4:23
    4. CPU and GPU 7:09
    5. CPU vs. GPU - Architectural difference 2:46
    6. Beyond Moore’s law 2:33
    7. Data Processing Unit (DPU) 6:43
    8. Network inside an AI centric Data Center 4:48
    9. Network fabric 4:41
    10. Ethernet vs. InfiniBand 7:04
    11. Converged Ethernet (CE) 2:27
    12. Storage inside an AI centric Data Center 4:19
    13. Cloud vs. On-Prem 4:09

  • Module 3 - Technology Stack

    Video Name Time
    1. Powering AI GPU Innovation 2:35
    2. Technology Stack 3:10
    3. Layer 1 - Physical Layer 3:51
    4. GPU on a Graphic Card 1:56
    5. DGX Platform 2:54
    6. DGX SuperPOD 1:53
    7. ConnectX 1:48
    8. BlueField DPUs 2:30
    9. Reference Architectures 1:32
    10. Understanding GPU Cores 4:57
    11. Comparing GPU Cores 4:17
    12. DGX Platform - Timeline 4:46
    13. DGX Platform - Deployment Options 3:35
    14. DGX A100 vs H100 4:01
    15. Layer 2: Data Movement and I/O Acceleration 0:56
    16. NVLink 8:01
    17. InfiniBand 2:03
    18. InfiniBand vs. Ethernet 1:41
    19. DMA and RDMA 6:07
    20. GPUDirect RDMA 2:22
    21. GPUDirect Storage 1:42
    22. Quick Comparison 1:31
    23. Layer 3: OS, Driver and Virtualization 2:16
    24. GPU Drivers 4:36
    25. GPU Virtualization 5:07
    26. vGPU vs. MIG - Part 1 7:47
    27. vGPU vs. MIG - Part 2 10:55
    28. Layer 4: Core Libraries 6:42
    29. Compute Unified Device Architecture (CUDA) 3:10
    30. Installing CUDA 2:07
    31. Collective Communications Library (NCCL) 3:39
    32. NVLink, NVSwitch, PCIe, RDMA vs. NCCL 3:42
    33. Layer 5: Monitoring and Management 2:21
    34. GPU Identification Utility 4:21
    35. Data Center GPU Manager (DCGM) 7:26
    36. Base Command Manager 5:31
    37. Which one to use? 2:02
    38. Layer 6: Applications & Vertical Solutions 3:46
    39. Summary 2:25
    40. AI Enterprise 3:01
    41. AI Factory 2:22

  • Module 4 - AI Workflows

    Video Name Time
    1. AI Workflows 5:20
    2. ML Frameworks 3:08
    3. The differentiator 1:40
    4. Model Training vs. Model Inference 7:45
    5. Job Scheduling vs. Container Orchestration 6:12
    6. Slurm vs Kubernetes 4:55
    7. Integration 2:28
    8. ML Ops - Analogy 4:15
    9. Why ML Ops? 3:41
    10. Tools supporting ML Ops 4:14

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