Google Professional Machine Learning Engineer |

Course Highlights
Expertise in Machine Learning: Acquire the skills to design, build, and deploy machine learning models grounded in Google Cloud’s core concepts and principles.
Data Preprocessing and Feature Engineering: Learn to prepare and transform data to extract meaningful features for machine learning.
Model Monitoring and Optimization: Understand how to monitor model performance and optimize machine learning solutions for ongoing success.
Orchestrate model training and deployment with TFX and Cloud AI Platform.
Operate deployed machine learning models effectively and efficiently.
Identify and use core technologies required to support effective MLOps.
Adopt the best CI/CD practices in the context of ML systems.
Devise a content-based recommendation engine.
Implement a collaborative filtering recommendation engine.
Advanced Deep Learning and Neural Networks

These highlights encapsulate the essential areas of focus and learning outcomes in the Professional Machine Learning Engineer Certification course.