Advanced Python for MLOps

You can learn Python on expert level based on real MLOps tasks

In this course, you will level up your Python to run production MLOps systems at scale. You will focus on speed, safety, and cost. Step by step, you will learn patterns that senior MLOps engineers use to keep services stable under load.

You will work with concurrency (threads and processes), high-performance I/O, Parquet and HDF5, and advanced logging. You will test with fixtures and mocks, use decorators and dynamic imports for plugins, and manage packages and dependencies the right way. You will also connect code to cloud SDKs (AWS/GCP/Azure), use Docker and Kubernetes Python clients, integrate ML platform SDKs like MLflow, and build production APIs with Flask and FastAPI.

By the end, you will be able to design and ship robust Python services for ML, with strong tests, clear runbooks, and easy ops. This course prepares you to join or lead modern MLOps projects with confidence.

Course Content

  • Course Introduction
  • About Your Instructor
  • Course Structure
  • GitHub repositories with MLOps projects
  • Dynamic imports & plugin patterns
  • Inheritance
  • Dunder or Magic Methods
  • Nested Exception Handling
  • pytest Fixtures
  • Mocks & Patches
  • High-performance file I/O (buffered, memory-mapped)
  • Basic Concepts
  • Thread-based parallelism (threading)
  • Process-based parallelism (multiprocessing)
  • Parallel Tasks Management
  • Subprocess Management
  • Synchronized Queue
  • Advanced Logging
  • Logging Handlers
  • Advanced Serialization: Parquet, HDF5, and Other Efficient Formats
  • Best Practices for Serialization
  • Cloud SDKs (AWS/GCP/Azure)
  • Docker & Kubernetes Python SDKs
  • ML platform SDKs (e.g., MLflow)
  • Declaring Dependencies
  • Packaging your Project
  • Decorators
  • Introduction to ML APIs
  • Introduction to Flask Framework
  • Building an API with Flask
  • Introduction to the FastAPI
  • Building an API with FastAPI
  • Python API Best Practices

Start learning high demand tech skills today

About Your Instructor

Hi, I’m Alex and I’ve spent over 20 years helping well known startups and enterprises introduce innovations. I also developed and taught Cloud&DevOps part for a Master’s Degree at the University.

In this course, I’ll show you what MLOps looks like in practice – step by step, with real tools and clear guidance.

You don’t need to be an expert. If you want to understand how to start or enforce your career as MLOps Engineer, not just in theory, but in real life, this course is for you. Let’s get started.

All courses are developed by experienced instructors with over 10 years of real-world industry expertise. We focus on delivering practical, up-to-date content – not just collecting enrollments, so that every course gives you real value.

Our courses meet high academic standards, and we’re actively working on certification to ensure they align with recognized best practices.

Each course includes video lectures, hands-on labs with screen recordings, quizzes, reading materials, GitHub repository with real project code, and a capstone project. This structure is designed to help you build practical, in-demand skills and knowledge that employers care about.

However, if you’re not satisfied for any reason, you can request a refund in accordance with our Refund Policy – your satisfaction matters to us.

It’s not just skills. It’s your next chapter.

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