Python Programming for MLOps - Production Environment - 2025
Optimize MLOps, AIOps, and DevOps Workflows with Python - Essential skills for productionalization
4.54 (42 reviews)
763
students
19.5 hours
content
Feb 2025
last update
$84.99
regular price
What you will learn
Apply Python confidently to infrastructure and operations tasks: Write clean, modular Python code using core principles, file handling, modules, and OOP.
Automate file-related operations: Efficiently manipulate, encrypt, and work with various file formats commonly used in DevOps, MLOps, and AIOps.
Create interactive command-line applications: Build CLIs with Python to automate tasks and streamline workflows.
Effectively manage Linux systems remotely: Use Python's Fabric library for remote execution and psutil for system monitoring
Create, manage, and publish Python packages: Organize code into reusable packages and distribute them on platforms like PyPI.
Utilize Docker for application deployments: Understand Docker image creation, containerization, and deployment.
Automate workflows with GitHub Actions: Design and configure CI/CD pipelines using GitHub Actions.
Implement CI/CD workflows utilizing AWS services: Design pipelines that leverage S3 for storage and EC2 instances for deployment.
Write tests specifically for MLOps projects: Ensure MLOps reliability and maintainability using Pytest.
Provision and manage infrastructure using code: Apply Infrastructure as Code (IaC) principles with Pulumi's Python SDK.
Experience a complete MLOps pipeline: Build an end-to-end MLOps solution integrating tools and concepts learned throughout the course.
Set up continuous monitoring for improved visibility: Implement monitoring and alerting using Prometheus and Grafana.
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udemy ID
4/8/2024
course created date
5/10/2024
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