Enroll Course: https://www.coursera.org/learn/ml-pipelines-google-cloud
If you’re looking to elevate your skills in machine learning operations and pipeline management, the ‘ML Pipelines on Google Cloud’ course on Coursera is an excellent resource. Taught by experienced ML Engineers and Trainers from Google Cloud, this course provides an in-depth look into building, managing, and automating ML pipelines using Google’s cutting-edge tools and frameworks.
The course begins with an introduction to TensorFlow Extended (TFX), Google’s robust production ML platform designed for efficient pipeline management and metadata handling. It then dives into pipeline components and orchestration with TFX, giving learners practical insights into designing scalable ML workflows.
One of the standout features of this course is its focus on automation through CI/CD practices, enabling continuous integration and deployment for ML models. The modules covering ML Metadata with TFX and continuous training across different SDKs, including KubeFlow and Google’s AI Platform Pipelines, are particularly valuable for those interested in MLOps and MLOps automation.
Additionally, the course explores other essential tools such as Cloud Composer and MLflow, providing a comprehensive overview of various platforms and their integration for seamless pipeline management. The hands-on approach with real-world scenarios makes this course highly practical for data scientists, ML engineers, and DevOps teams.
I highly recommend this course for anyone aiming to streamline their ML workflows, learn about Google Cloud’s powerful tools, or prepare for careers in MLOps. Whether you’re a beginner or an experienced professional, the modules on pipeline orchestration, automation, and metadata management are invaluable for advancing your skills and implementing efficient ML pipelines in production environments.
Enroll Course: https://www.coursera.org/learn/ml-pipelines-google-cloud