Enroll Course: https://www.udemy.com/course/machine-learning-on-google-cloud-platform/
In today’s data-driven world, leveraging cloud platforms for machine learning is no longer a luxury but a necessity. For data scientists and AI practitioners, understanding how to harness the power of cloud services can significantly enhance project efficiency and scalability. If you’re looking to transition from other cloud providers like AWS or Azure, or if you’re new to cloud ML altogether, the ‘Machine Learning on Google Cloud (Vertex AI) – Hands on!’ course on Udemy is an exceptional starting point.
This comprehensive course is expertly designed to cater to a broad audience, from beginners taking their first steps into cloud computing to seasoned AI professionals seeking to expand their GCP expertise. It begins with a foundational overview of the Google Cloud Platform (GCP), guiding you through account creation and familiarizing you with essential GCP services. Before diving into the AI-specific offerings, the course provides crucial insights into core components like Compute, Storage, Databases, IAM, and Analytics, complete with practical demonstrations. This solid grounding ensures you understand the ecosystem in which your ML models will operate.
The latter three sections are where the magic truly happens, focusing intensely on GCP’s AI services. You’ll gain hands-on experience with AutoML for tabular, image, and text data, learning to build and deploy models and retrieve predictions via APIs. The AI Platform section delves into both GUI and coding approaches for model creation and deployment, job management, and model evaluation. A significant highlight is the introduction to Kubeflow pipelines, a powerful tool for orchestrating complex ML workflows.
Finally, the course culminates with an in-depth exploration of Vertex AI, GCP’s unified ML platform. Here, you’ll master model creation using AutoML and custom training, including the critical step of hyperparameter optimization. You’ll also learn to build Kubeflow pipelines integrating both AutoML and custom models, and get acquainted with the essential Feature Store for managing ML features. The ‘Hands on!’ aspect of the course title is truly lived up to, with practical exercises throughout that solidify your understanding and build real-world skills.
For anyone serious about advancing their machine learning capabilities on Google Cloud, this course is a must-have. It’s well-structured, covers a vast array of essential services and techniques, and provides the practical experience needed to confidently deploy and manage ML solutions on GCP.
Enroll Course: https://www.udemy.com/course/machine-learning-on-google-cloud-platform/