Description

Build and Deploy Secure AI Workloads with Docker. This course is a practical guide to securely deploying, running, and managing large language models locally using Docker Model Runner to develop AI applications without the need for cloud services. This course explores how to leverage the capabilities of Large Language Models (LLM) on-premises using Docker Model Runner. DevOps Ambassador and leading Docker expert Pawel Piwosz walks you through the steps of deploying, configuring, and running language models locally, so that they can be accessed and managed both from containers and on the host system. In this course, students learn how to receive, manage, and organize pre-built models from Docker Hub, as well as package and distribute their own models. A key part of this course is learning how to integrate and connect native language models into software and applications using the standard OpenAI API. This course provides practical solutions for those looking to build prototypes, maintain full data privacy, increase security, and reduce processing costs without relying on cloud infrastructure. Along the way, learners learn how to manage powerful AI models in isolated and secure environments without the need for cloud computing. The main focus of the course is on the practical concepts of Language Model Operations (LLMOps) so that developers can run AI-based applications with high productivity and according to real-world standards.

What you will learn

• Setting up and configuring the Docker Model Runner tool to run large language models locally
• Invoke and manage pre-built AI models from Docker Hub
• Packaging, building, and distributing custom models based on Docker containers
• Communicate and integrate local models with applications via the OpenAI API
• Reduce data inference costs and eliminate dependency on cloud service providers
• Improving data security and privacy in artificial intelligence projects
• Applying principles and practical concepts in the field of Linguistic Model Operations (LLMOps)

This course is suitable for people who:

• Software developers and AI engineers who want to run language models locally
• DevOps professionals looking to implement and manage AI containers in their workplaces
• Researchers and programmers who need to maintain the privacy and security of sensitive data in their projects
• People who want to reduce the costs associated with cloud computing and develop project prototypes for free
• Those interested in learning specialized Docker tools and integrating them with AI-based systems

Build and Deploy Secure AI Workloads with Docker Course Details

• Publisher: LinkedIn
• Instructor: Pawel Piwosz

• Education level: Intermediate
• Training duration: 2 hours and 10 minutes

Course topics

Course images

Sample course video

Download link

Download file – 377 MB

Rapidgator link

Download File – 377 MB

File(s) password: www.downloadly.ir

File size

377 MB