In a very important step to increase tech skills worldwide, Google announced the use of seven free courses on MLOps (Machine learning operations). The goal of the project is to provide trained project specialists with sufficient skills and knowledge to implement, monitor, and optimize the system of machine learning using practical tools.

Courses Tailored for Learners:

Such programs are intended for learners with skills at the intermediate level as well as those more skilled in MLOps essentials which include deployment, automation, continuous delivery, and feature management.

1.Machine Learning Operations (MLOps): Getting Started:  Novice, as well as seasoned engineers, can learn and practice core MLOps technologies and guiding ideas fundamental for the successfully executed machine learning deployment and management on Google Cloud.

2. MLOps: CD and automation pipelines and ML: The objective of this course is to understand and discuss the procedures set for the presence and automation of CI, CD, and CT methods for ML systems. Data science and ML are gaining popular acceptance as core service platforms and widening the gap in resolving complex real-world problems or transforming industries, providing value in all domains.

3. Advanced Automation: Continuous integration, delivery, and training form the heart of machine learning and are essential knowledge to have. This course is key in knowing how work still can be accomplished even in machine learning operations.

4. Vertex AI and ML Solutions: Skill badge course for hands-on job course and learning enterprise-level machine learning topics like customer behavior prediction and sentiment analysis.

5. ML Pipelines on Google Cloud: Learn the ways that TensorFlow Extended (TFX) is utilized by the front runners from google for production optimization of the ML pipelines.

6. Feature Management with Vertex AI: Participants will interact with Vertex AI Feature Store which will improve their expertise in maintaining production systems along with ML features stipulated therein.

7. Production Machine Learning Systems: This course is concerned with diverse classes of smart ML systems; the emphasis being placed on programmatic applications and modeling strategies for drastic scenarios.

Enrollment Open Now

This excellent prospect of professional development is a twofold win that impacts techies' ability to keep deep in the rapidly changing domain. The enrollment is already open, those who are interested have been urged to hasten their registration so as not to miss the rare opportunity presented by the learning experience.