AIOps: CI/CD for AI Systems

Overview

DevOps is a concept that has been around a long time and has been applied to ML and, recently, LLMs. In this course, AIOps:

CI/CD for AI Systems, you’ll learn to apply CI/CD, a fundamental concept of DevOps, to ML, AI, and LLMs.

First, you’ll explore how CI/CD pipelines work with ML models. Next, you’ll discover how to deploy to cloud environments using a CI/CD pipeline.

Finally, you’ll learn how to automatically test the pipeline at all stages. When you’re finished with this course, you’ll have the skills and knowledge of CI/CD pipelines needed to produce and apply these pipelines to your own ML/AI/LLM models.

Syllabus

• Introduction to AIOps and CI/CD for AI
Overview of DevOps principles
Introduction to CI/CD concepts
Importance of CI/CD in AI and ML
• CI/CD Pipelines for Machine Learning Models
Designing a CI/CD pipeline for ML
Tools and platforms for ML CI/CD (Jenkins, GitLab, etc.)
Version control and model tracking (Git, DVC)
• Implementing CI/CD Pipelines for AI
Integrating CI/CD with machine learning workflows
Automating data preprocessing and feature engineering
Continuous training and validation of models
• Deploying AI Models with CI/CD
Strategies for deploying ML models to cloud environments
Using cloud services (AWS, Azure, GCP) for model deployment
Infrastructure as code for AI systems (Terraform, Ansible)
• CI/CD for Large Language Models (LLMs)
Special considerations for LLMs in CI/CD
Techniques for efficient LLM deployment
Monitoring and updating deployed LLMs
• Testing in CI/CD Pipelines
Automatic testing frameworks and strategies
Unit testing and integration testing for AI systems
Ensuring model performance and reliability through testing
• Advanced CI/CD Topics
Handling data drift and model retraining
Implementing A/B testing and canary releases for AI models
Security and compliance in AI CI/CD pipelines
• Case Studies and Real-world Applications
Evaluation of successful CI/CD implementations in AI
Lessons learned from industry leaders
• Course Conclusion and Practical Application
Best practices for CI/CD in AI development
Hands-on project: Building a CI/CD pipeline for a sample AI model

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Taught by

David Harris

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Subjects

Computer Science