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Udemy - Advanced Bash Shell Scripting - Automation for DevOps torrent


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Health:
 seeds: 8, leechers: 1
Torrent language: English English
Total Size: 1.80 GB
Number of files:
114   
Uploader:
freecoursewb
Torrent added:2026-05-01 09:33:44

Download Udemy - Advanced Bash Shell Scripting - Automation for DevOps torrent




Torrent Description
Advanced Bash Shell Scripting: Automation for DevOps
https://WebToolTip.com
Published 4/2026

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Language: English | Duration: 8h 14m | Size: 1.78 GB
Master Bash, NVIDIA Blackwell, and DORA Compliance in 100 Sovereign Labs.
What you'll learn

Architect production-grade, idempotent infrastructure using advanced Bash shell scripting to eliminate reliance on brittle abstraction layers.

Deploy multi-node NVIDIA Blackwell GPU clusters using NVLink Switch fabrics and IMEX domains for scalable AI inference.

Codify 2026 regulatory mandates, including DORA and the EU AI Act, directly into autonomous infrastructure execution logic.

Master Zero-Trust security primitives, including hardware-rooted TPM 2.0 attestation and mTLS mutual authentication for secure pipelines.

Orchestrate autonomous AI agents using the Model Context Protocol (MCP) to standardize integrations between LLMs and enterprise data.

Implement self-healing AIOps mechanisms that detect, remediate, and audit system failures in real-time without human intervention.

Engineer high-speed data pipelines using awk, sed, and Pydantic-validated CLI wrappers for terabyte-scale log processing.

Design air-gapped deployment environments for decentralized research clusters that function without external internet access.
Requirements

Operating System: Access to a modern Linux distribution (Ubuntu 24.04+, Fedora) or macOS with a terminal environment. Technical Baseline: A basic understanding of the command line and a desire to move beyond "copy-paste" coding. Software: A text editor (VS Code, Vim, or Cursor) and Python 3.12+ installed for integration labs. Hardware: A machine with at least 8GB of RAM; no physical NVIDIA GPU is required, as the course provides simulated Blackwell environments via cloud labs.

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