Build and Deploy Secure AI Workloads with Docker

Category : Other
Type: Tutorials
Language: English
Total Size: 383.8 MB
Uploaded By: freecoursewb
Downloads: 31520
Last checked: Jun. 11th '26
Date uploaded: Jun. 11th '26
Seeders: 12351
Leechers: 8870
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About Build and Deploy Secure AI Workloads with Docker

Overview

Build and Deploy Secure AI Workloads with Docker https://WebToolTip.com Released 6/2026 With Pawel Piwosz MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 10m | Size: 383.8 MB Learn how to run, manage and integrate AI workloads into Docker native toolset, like Docker Model Runner, MCP Toolkit, and Offload. Course details Unlock the power of large language models (LLMs) on your local machine using D

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The total size of Build and Deploy Secure AI Workloads with Docker is 383.8 MB.

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Build and Deploy Secure AI Workloads with Docker

https://WebToolTip.com

Released 6/2026
With Pawel Piwosz
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 10m | Size: 383.8 MB

Learn how to run, manage and integrate AI workloads into Docker native toolset, like Docker Model Runner, MCP Toolkit, and Offload.

Course details
Unlock the power of large language models (LLMs) on your local machine using Docker Model Runner. In this course, join Docker Captain and DevOps Institute Ambassador Pawel Piwosz as he shows you how to set up and configure Docker Model Runner to run LLMs locally—making them accessible from both containers and the host system. Explore how to pull and manage prebuilt models from Docker Hub, as well as package and distribute your own models. Along the way, learn how to integrate local LLMs into your applications using the familiar OpenAI API interface. Whether you're building prototypes, safeguarding privacy, or reducing inference costs, this course covers the tools you need to know to run powerful models without relying on the cloud.

Skills covered
Large Language Model Operations (LLMOps), Docker Products, Artificial Intelligence (AI), Docker