MLOps – Deployment and production monitoring

Main Speaker

Learning Tracks

Course ID

42788

Date

01/12/2025

Time

Daily seminar
9:00-16:30

Location

John Bryce ECO Tower, Homa Umigdal 29 Tel-Aviv

Overview

This seminar is designed to provide a comprehensive introduction to MLOps, blending theoretical concepts with hands-on practical skills. The day will be tailored towards data engineers and professionals who are already familiar with the basics of data management, cloud services, and programming, aiming to extend their expertise into the realm of MLOps. Participants will gain insights into how to streamline the deployment, monitoring, and management of machine learning models at scale, using industry-standard tools and practices.

Who Should Attend

Software developers, Data engineers, machine learning engineers and DevOps professionals who are looking to enhance their skills in deploying and managing machine learning models at scale.

Prerequisites

working knowledge of Python, SQL, and version control systems (Git).

Course Contents

Part 1
  • Overview of MLOps: Definition, Importance, and Industry Applications
  • Key Concepts: Model Versioning and Monitoring
  • The MLOps Lifecycle: From Data Ingestion to Model Deployment
Part 2
  • Efficient Data Management and Pipelines with Python
  • SQL Techniques for Handling Large-Scale Data
  • Automating Data Workflows with Apache Airflow
  • Hands-on: Prepare data for AI Application
Part 3
  • Triton & MLOps Foundations
  • Packaging & Serving with Triton
  • Hands-on: Build and AI application
Part 4
  • Best Practices for Using Git in MLOps Projects
  • Managing Code and Model Versioning
  • Collaborative Workflows in MLOps with GitHub/GitLab
  • Automating Model Retraining and Deployment
  • Hands-on: Package an AI application

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