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Udemy - SoAI-Certified Professional - AI Infrastructure (NCP-AII)

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Udemy - SoAI-Certified Professional - AI Infrastructure (NCP-AII)
Language: English
Category: Other
Size: 102 bytes
Added: June 20, 2026, 1:43 a.m.
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Files:
  1. Get Bonus Downloads Here.url 180 bytes
  2. 1. Certificate of Completion.en_US.srt 690 bytes
  3. 1. Certificate of Completion.mp4 10.9 MB
  4. 2. Introduction to NVIDIA-Certified Professional AI Infrastructure (NCP-AII).en_US.srt 3.6 KB
  5. 2. Introduction to NVIDIA-Certified Professional AI Infrastructure (NCP-AII).mp4 9.3 MB
  6. 1. Quiz Module 9 Real-World Projects and Enterprise Workflows.html 23.4 KB
  7. 43. Case Study Building an AI Supercomputer.en_US.srt 6.1 KB
  8. 43. Case Study Building an AI Supercomputer.mp4 18.1 MB
  9. 44. Case Study Multi-Tenant AI Infrastructure for Healthcare.en_US.srt 6.5 KB
  10. 44. Case Study Multi-Tenant AI Infrastructure for Healthcare.mp4 22.9 MB
  11. 45. End-to-End Workflow Data → Train → Deploy → Monitor.en_US.srt 5.6 KB
  12. 45. End-to-End Workflow Data → Train → Deploy → Monitor.mp4 13.3 MB
  13. 46. Lab Design and Present a Scalable AI Infrastructure.html 5.6 KB
  14. 46. Module9_Lab.pdf 121.6 KB
  15. 47. Peer Review.html 5.4 KB
  16. 47. PeerReview.pdf 44.7 KB
  17. 2. Mock Test 60 Questions.html 49.0 KB
  18. 48. Exam Blueprint and Common Pitfalls.en_US.srt 4.3 KB
  19. 48. Exam Blueprint and Common Pitfalls.mp4 9.8 MB
  20. 49. 10.2FlashCards.pdf 90.2 KB
  21. 49. Flashcards Concepts, Commands, Tools.html 5.8 KB
  22. 50. Capstone Project End-to-End AI Infrastructure Design.html 5.9 KB
  23. 50. CapstoneProject.pdf 94.3 KB
  24. 51. Certification Pathways and Next Steps.en_US.srt 4.5 KB
  25. 51. Certification Pathways and Next Steps.mp4 9.1 MB
  26. 3. Introduction to AI Infrastructure Design.en_US.srt 6.6 KB
  27. 3. Introduction to AI Infrastructure Design.mp4 14.0 MB
  28. 4. Role of GPUs in AI Workloads.en_US.srt 5.2 KB
  29. 4. Role of GPUs in AI Workloads.mp4 11.1 MB
  30. 5. CPU vs GPU vs DPU Architectures.en_US.srt 4.8 KB
  31. 5. CPU vs GPU vs DPU Architectures.mp4 10.1 MB
  32. 6. GPU Acceleration for AI ML Pipelines.en_US.srt 5.2 KB
  33. 6. GPU Acceleration for AI ML Pipelines.mp4 11.2 MB
  34. 7. NVIDIA Ecosystem Overview (CUDA, Triton, NGC).en_US.srt 5.2 KB
  35. 7. NVIDIA Ecosystem Overview (CUDA, Triton, NGC).mp4 12.0 MB
  36. 10. Virtual GPUs (vGPU) Setup and Use Cases.en_US.srt 5.9 KB
  37. 10. Virtual GPUs (vGPU) Setup and Use Cases.mp4 13.7 MB
  38. 11. GPU Workload Scheduling with Kubernetes.en_US.srt 5.9 KB
  39. 11. GPU Workload Scheduling with Kubernetes.mp4 13.2 MB
  40. 12. Hands-on Lab Configure MIG on A100.html 5.6 KB
  41. 12. Lab2.pdf 208.5 KB
  42. 8. MIG (Multi-Instance GPU) Configuration.en_US.srt 6.0 KB
  43. 8. MIG (Multi-Instance GPU) Configuration.mp4 13.7 MB
  44. 9. GPU Sharing and Isolation Techniques.en_US.srt 5.7 KB
  45. 9. GPU Sharing and Isolation Techniques.mp4 12.6 MB
  46. 13. Storage Architectures for AI Workloads (local, shared, object).en_US.srt 5.3 KB
  47. 13. Storage Architectures for AI Workloads (local, shared, object).mp4 15.1 MB
  48. 14. High-Speed Networking NVLink, Infiniband, RDMA.en_US.srt 5.7 KB
  49. 14. High-Speed Networking NVLink, Infiniband, RDMA.mp4 13.5 MB
  50. 15. Data Movement Bottlenecks and Optimization.en_US.srt 5.6 KB
  51. 15. Data Movement Bottlenecks and Optimization.mp4 12.0 MB
  52. 16. AI Data Pipeline Design (ETL + Training + Inference).en_US.srt 5.4 KB
  53. 16. AI Data Pipeline Design (ETL + Training + Inference).mp4 11.5 MB
  54. 17. Lab Design an End-to-End Data Pipeline for AI.html 5.6 KB
  55. 17. Lab3.pdf 249.5 KB
  56. 18. Kubernetes for GPU-Orchestrated AI Workloads.en_US.srt 4.2 KB
  57. 18. Kubernetes for GPU-Orchestrated AI Workloads.mp4 9.5 MB
  58. 19. Helm, Operators, and Cluster Autoscaling.en_US.srt 3.8 KB
  59. 19. Helm, Operators, and Cluster Autoscaling.mp4 8.8 MB
  60. 20. Integrating Slurm, Kubeflow, and MLflow.en_US.srt 4.8 KB
  61. 20. Integrating Slurm, Kubeflow, and MLflow.mp4 10.8 MB
  62. 21. Cluster Topologies (On-prem, Cloud, Hybrid).en_US.srt 4.8 KB
  63. 21. Cluster Topologies (On-prem, Cloud, Hybrid).mp4 10.3 MB
  64. 22. Lab Deploy Multi-GPU Training Job on Kubernetes.html 5.6 KB
  65. 22. Lab4.pdf 179.2 KB
  66. 23. Profiling GPU Workloads (Nsight, DLProf, nvtop).en_US.srt 5.6 KB
  67. 23. Profiling GPU Workloads (Nsight, DLProf, nvtop).mp4 11.5 MB
  68. 24. GPU Metrics, Telemetry & Alerting Tools.en_US.srt 5.6 KB
  69. 24. GPU Metrics, Telemetry & Alerting Tools.mp4 11.8 MB
  70. 25. TensorRT and Model Optimization.en_US.srt 5.4 KB
  71. 25. TensorRT and Model Optimization.mp4 11.0 MB
  72. 26. Bottleneck Diagnosis and Tuning.en_US.srt 5.5 KB
  73. 26. Bottleneck Diagnosis and Tuning.mp4 11.9 MB
  74. 27. Lab Optimize Inference Pipeline with TensorRT.html 5.8 KB
  75. 27. Lab5.pdf 186.8 KB
  76. 28. Securing GPU-Powered Workloads.en_US.srt 5.5 KB
  77. 28. Securing GPU-Powered Workloads.mp4 12.0 MB
  78. 29. Encryption and Access Control (DPUs, DOCA).en_US.srt 6.2 KB
  79. 29. Encryption and Access Control (DPUs, DOCA).mp4 14.3 MB
  80. 30. Role-Based Access Control (RBAC) for AI Clusters.en_US.srt 6.3 KB
  81. 30. Role-Based Access Control (RBAC) for AI Clusters.mp4 13.9 MB
  82. 31. Regulatory Compliance GDPR, HIPAA, FedRAMP.en_US.srt 6.5 KB
  83. 31. Regulatory Compliance GDPR, HIPAA, FedRAMP.mp4 14.7 MB
  84. 32. Lab Apply Security Policies in AI Infrastructure.html 5.8 KB
  85. 32. Lab6.pdf 180.6 KB
  86. 33. Edge vs Cloud AI – Infrastructure Implications.en_US.srt 4.0 KB
  87. 33. Edge vs Cloud AI – Infrastructure Implications.mp4 9.2 MB
  88. 34. NVIDIA Jetson and Orin for Edge AI.en_US.srt 4.9 KB
  89. 34. NVIDIA Jetson and Orin for Edge AI.mp4 10.8 MB
  90. 35. Federated Learning and Distributed Inference.en_US.srt 4.6 KB
  91. 35. Federated Learning and Distributed Inference.mp4 10.4 MB
  92. 36. Use Cases Smart Cities, Retail, Industrial IoT.en_US.srt 4.1 KB
  93. 36. Use Cases Smart Cities, Retail, Industrial IoT.mp4 8.8 MB
  94. 37. Lab Deploy AI Model to Jetson Nano.html 5.9 KB
  95. 37. Module7_lab.pdf 272.0 KB
  96. 38. Using NGC Catalog for Pretrained Models.en_US.srt 7.3 KB
  97. 38. Using NGC Catalog for Pretrained Models.mp4 15.4 MB
  98. 39. Triton Inference Server – Overview and Architecture.en_US.srt 8.0 KB
  99. 39. Triton Inference Server – Overview and Architecture.mp4 15.9 MB
  100. 40. Model Ensemble and Multi-Framework Serving.en_US.srt 6.8 KB
  101. 40. Model Ensemble and Multi-Framework Serving.mp4 14.3 MB
  102. 41. Lab Deploy Triton with TensorFlow and ONNX Models.html 5.7 KB
  103. 41. Module8_Lab.pdf 150.6 KB
  104. 42. Serving at Scale – Load Balancing and HA Design.en_US.srt 5.4 KB
  105. 42. Serving at Scale – Load Balancing and HA Design.mp4 15.2 MB
  106. Bonus Resources.txt 70 bytes

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