Hands-on Python for MLOps

Build powerful APIs, tools, and scripts with Python

Use Python to create APIs and automation scripts for machine learning operations. Learn to leverage APIs, build CLI tools, and develop web services. If you are new to Machine Learning Operations or want to know more about the foundations of Python for MLOps, this course will walk you through the basics.

In this course, you'll learn how to use Python for automation, APIs, and building useful command-line interfaces. We'll cover consuming APIs, creating CLI tools, packaging projects, and building web services to expose machine learning models.

The course includes hands-on examples and projects so you can apply what you learn right away. By the end of the course, you'll have practical skills to automate workflows and develop interfaces for machine learning.

This course includes GitHub repositories you can reference:

• Python CLI Examples
• Basic Python CLI
• Web API with Python and Hugging Face models

Learn objectives

• Consume and use APIs and SDKs in Python
• Create command-line programs for automation
• Develop web services and APIs with Python frameworks
• Package Python projects for distribution
• Apply skills to build useful interfaces for ML models

Lesson 1: Working with APIs in Python

Lesson Outline

• Overview of APIs and SDKs
• Using the Requests Library
• Consuming REST APIs
• Python SDKs like NumPy and SciPy
• Project: Building a Python script using APIs

Lesson 2: Building Command-line Interfaces

Lesson Outline

• Intro to automation with CLI tools
• Parsing arguments and options
• Organizing code into modules
• Python packaging for distribution
• Project: CLI tool for machine learning

Lesson 3: Developing Web APIs

Lesson Outline

• REST API concepts
• Web frameworks like Flask and FastAPI
• Building an API with Flask
• Developing APIs with FastAPI
• OpenAPI specs and documentation
• Project: Web API for movie recommendations

About your instructor

Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his past experience as a Linux system administrator is seen throughout this course, where you will get a first-hand experience with high-level knowledge and practical examples.

Resources

• Pytest Master Class

• Practical MLOps book