The MLOps Coding Course is a practical, project-based program designed to teach how to bridge the gap between software engineering and data science. It focuses on building real-world machine learning systems that are scalable, maintainable, and ready for production.
The course begins with foundational system setup, including Python environment configuration, project management using modern tools like uv, and best practices for structuring ML projects. You will also learn essential version control skills using Git and GitHub, which are critical for collaborative ML development.
As the course progresses, you will explore development environments such as VS Code and learn how to efficiently manage notebooks, imports, and project configurations. These skills help create clean and reproducible machine learning workflows.
A major focus is placed on building strong engineering habits for MLOps, including modular code design, reproducibility, and proper project organization. The course emphasizes real-world workflows rather than just theoretical concepts.
By combining software engineering practices with machine learning development, this course prepares you to build production-grade AI systems in
