Torrent details for "Udemy - SoAI-Certified Professional - AI Infrastructure (NCP-AII)" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
English
Total Size:
102 bytes
Info Hash:
3F0CA5D54BFB693E76DF98A4794B6C12973D20D5
Added By:
Added:
June 20, 2026, 1:43 a.m.
Stats:
|
(Last updated: June 20, 2026, 1:43 a.m.)
| File | Size |
|---|---|
| Get Bonus Downloads Here.url | 180 bytes |
| 1. Certificate of Completion.en_US.srt | 690 bytes |
| 1. Certificate of Completion.mp4 | 10.9 MB |
| 2. Introduction to NVIDIA-Certified Professional AI Infrastructure (NCP-AII).en_US.srt | 3.6 KB |
| 2. Introduction to NVIDIA-Certified Professional AI Infrastructure (NCP-AII).mp4 | 9.3 MB |
| 1. Quiz Module 9 Real-World Projects and Enterprise Workflows.html | 23.4 KB |
| 43. Case Study Building an AI Supercomputer.en_US.srt | 6.1 KB |
| 43. Case Study Building an AI Supercomputer.mp4 | 18.1 MB |
| 44. Case Study Multi-Tenant AI Infrastructure for Healthcare.en_US.srt | 6.5 KB |
| 44. Case Study Multi-Tenant AI Infrastructure for Healthcare.mp4 | 22.9 MB |
| 45. End-to-End Workflow Data → Train → Deploy → Monitor.en_US.srt | 5.6 KB |
| 45. End-to-End Workflow Data → Train → Deploy → Monitor.mp4 | 13.3 MB |
| 46. Lab Design and Present a Scalable AI Infrastructure.html | 5.6 KB |
| 46. Module9_Lab.pdf | 121.6 KB |
| 47. Peer Review.html | 5.4 KB |
| 47. PeerReview.pdf | 44.7 KB |
| 2. Mock Test 60 Questions.html | 49.0 KB |
| 48. Exam Blueprint and Common Pitfalls.en_US.srt | 4.3 KB |
| 48. Exam Blueprint and Common Pitfalls.mp4 | 9.8 MB |
| 49. 10.2FlashCards.pdf | 90.2 KB |
| 49. Flashcards Concepts, Commands, Tools.html | 5.8 KB |
| 50. Capstone Project End-to-End AI Infrastructure Design.html | 5.9 KB |
| 50. CapstoneProject.pdf | 94.3 KB |
| 51. Certification Pathways and Next Steps.en_US.srt | 4.5 KB |
| 51. Certification Pathways and Next Steps.mp4 | 9.1 MB |
| 3. Introduction to AI Infrastructure Design.en_US.srt | 6.6 KB |
| 3. Introduction to AI Infrastructure Design.mp4 | 14.0 MB |
| 4. Role of GPUs in AI Workloads.en_US.srt | 5.2 KB |
| 4. Role of GPUs in AI Workloads.mp4 | 11.1 MB |
| 5. CPU vs GPU vs DPU Architectures.en_US.srt | 4.8 KB |
| 5. CPU vs GPU vs DPU Architectures.mp4 | 10.1 MB |
| 6. GPU Acceleration for AI ML Pipelines.en_US.srt | 5.2 KB |
| 6. GPU Acceleration for AI ML Pipelines.mp4 | 11.2 MB |
| 7. NVIDIA Ecosystem Overview (CUDA, Triton, NGC).en_US.srt | 5.2 KB |
| 7. NVIDIA Ecosystem Overview (CUDA, Triton, NGC).mp4 | 12.0 MB |
| 10. Virtual GPUs (vGPU) Setup and Use Cases.en_US.srt | 5.9 KB |
| 10. Virtual GPUs (vGPU) Setup and Use Cases.mp4 | 13.7 MB |
| 11. GPU Workload Scheduling with Kubernetes.en_US.srt | 5.9 KB |
| 11. GPU Workload Scheduling with Kubernetes.mp4 | 13.2 MB |
| 12. Hands-on Lab Configure MIG on A100.html | 5.6 KB |
| 12. Lab2.pdf | 208.5 KB |
| 8. MIG (Multi-Instance GPU) Configuration.en_US.srt | 6.0 KB |
| 8. MIG (Multi-Instance GPU) Configuration.mp4 | 13.7 MB |
| 9. GPU Sharing and Isolation Techniques.en_US.srt | 5.7 KB |
| 9. GPU Sharing and Isolation Techniques.mp4 | 12.6 MB |
| 13. Storage Architectures for AI Workloads (local, shared, object).en_US.srt | 5.3 KB |
| 13. Storage Architectures for AI Workloads (local, shared, object).mp4 | 15.1 MB |
| 14. High-Speed Networking NVLink, Infiniband, RDMA.en_US.srt | 5.7 KB |
| 14. High-Speed Networking NVLink, Infiniband, RDMA.mp4 | 13.5 MB |
| 15. Data Movement Bottlenecks and Optimization.en_US.srt | 5.6 KB |
| 15. Data Movement Bottlenecks and Optimization.mp4 | 12.0 MB |
| 16. AI Data Pipeline Design (ETL + Training + Inference).en_US.srt | 5.4 KB |
| 16. AI Data Pipeline Design (ETL + Training + Inference).mp4 | 11.5 MB |
| 17. Lab Design an End-to-End Data Pipeline for AI.html | 5.6 KB |
| 17. Lab3.pdf | 249.5 KB |
| 18. Kubernetes for GPU-Orchestrated AI Workloads.en_US.srt | 4.2 KB |
| 18. Kubernetes for GPU-Orchestrated AI Workloads.mp4 | 9.5 MB |
| 19. Helm, Operators, and Cluster Autoscaling.en_US.srt | 3.8 KB |
| 19. Helm, Operators, and Cluster Autoscaling.mp4 | 8.8 MB |
| 20. Integrating Slurm, Kubeflow, and MLflow.en_US.srt | 4.8 KB |
| 20. Integrating Slurm, Kubeflow, and MLflow.mp4 | 10.8 MB |
| 21. Cluster Topologies (On-prem, Cloud, Hybrid).en_US.srt | 4.8 KB |
| 21. Cluster Topologies (On-prem, Cloud, Hybrid).mp4 | 10.3 MB |
| 22. Lab Deploy Multi-GPU Training Job on Kubernetes.html | 5.6 KB |
| 22. Lab4.pdf | 179.2 KB |
| 23. Profiling GPU Workloads (Nsight, DLProf, nvtop).en_US.srt | 5.6 KB |
| 23. Profiling GPU Workloads (Nsight, DLProf, nvtop).mp4 | 11.5 MB |
| 24. GPU Metrics, Telemetry & Alerting Tools.en_US.srt | 5.6 KB |
| 24. GPU Metrics, Telemetry & Alerting Tools.mp4 | 11.8 MB |
| 25. TensorRT and Model Optimization.en_US.srt | 5.4 KB |
| 25. TensorRT and Model Optimization.mp4 | 11.0 MB |
| 26. Bottleneck Diagnosis and Tuning.en_US.srt | 5.5 KB |
| 26. Bottleneck Diagnosis and Tuning.mp4 | 11.9 MB |
| 27. Lab Optimize Inference Pipeline with TensorRT.html | 5.8 KB |
| 27. Lab5.pdf | 186.8 KB |
| 28. Securing GPU-Powered Workloads.en_US.srt | 5.5 KB |
| 28. Securing GPU-Powered Workloads.mp4 | 12.0 MB |
| 29. Encryption and Access Control (DPUs, DOCA).en_US.srt | 6.2 KB |
| 29. Encryption and Access Control (DPUs, DOCA).mp4 | 14.3 MB |
| 30. Role-Based Access Control (RBAC) for AI Clusters.en_US.srt | 6.3 KB |
| 30. Role-Based Access Control (RBAC) for AI Clusters.mp4 | 13.9 MB |
| 31. Regulatory Compliance GDPR, HIPAA, FedRAMP.en_US.srt | 6.5 KB |
| 31. Regulatory Compliance GDPR, HIPAA, FedRAMP.mp4 | 14.7 MB |
| 32. Lab Apply Security Policies in AI Infrastructure.html | 5.8 KB |
| 32. Lab6.pdf | 180.6 KB |
| 33. Edge vs Cloud AI – Infrastructure Implications.en_US.srt | 4.0 KB |
| 33. Edge vs Cloud AI – Infrastructure Implications.mp4 | 9.2 MB |
| 34. NVIDIA Jetson and Orin for Edge AI.en_US.srt | 4.9 KB |
| 34. NVIDIA Jetson and Orin for Edge AI.mp4 | 10.8 MB |
| 35. Federated Learning and Distributed Inference.en_US.srt | 4.6 KB |
| 35. Federated Learning and Distributed Inference.mp4 | 10.4 MB |
| 36. Use Cases Smart Cities, Retail, Industrial IoT.en_US.srt | 4.1 KB |
| 36. Use Cases Smart Cities, Retail, Industrial IoT.mp4 | 8.8 MB |
| 37. Lab Deploy AI Model to Jetson Nano.html | 5.9 KB |
| 37. Module7_lab.pdf | 272.0 KB |
| 38. Using NGC Catalog for Pretrained Models.en_US.srt | 7.3 KB |
| 38. Using NGC Catalog for Pretrained Models.mp4 | 15.4 MB |
| 39. Triton Inference Server – Overview and Architecture.en_US.srt | 8.0 KB |
| 39. Triton Inference Server – Overview and Architecture.mp4 | 15.9 MB |
| 40. Model Ensemble and Multi-Framework Serving.en_US.srt | 6.8 KB |
| 40. Model Ensemble and Multi-Framework Serving.mp4 | 14.3 MB |
| 41. Lab Deploy Triton with TensorFlow and ONNX Models.html | 5.7 KB |
| 41. Module8_Lab.pdf | 150.6 KB |
| 42. Serving at Scale – Load Balancing and HA Design.en_US.srt | 5.4 KB |
| 42. Serving at Scale – Load Balancing and HA Design.mp4 | 15.2 MB |
| Bonus Resources.txt | 70 bytes |
Name
DL
Uploader
Size
S/L
Added
-
102 bytes
[12
/
3]
2026-06-20
| Uploaded by anonymous | Size 102 bytes | Health [ 12 /3 ] | Added 2026-06-20 |
NOTE
SOURCE: Udemy - SoAI-Certified Professional - AI Infrastructure (NCP-AII)
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
None
×