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via Udemy |
Go to Course: https://www.udemy.com/course/machine-learning-on-google-cloud-platform/
**Review and Recommendation for "Machine Learning on Google Cloud (Vertex AI) - Hands on!" on Coursera** If you're a data scientist or AI practitioner eager to expand your expertise into the cloud platform domain, especially Google Cloud Platform (GCP), then the course **"Machine Learning on Google Cloud (Vertex AI) - Hands on!"** is an excellent choice for you. **Overview & Content:** This course provides a comprehensive, hands-on introduction to deploying machine learning models on Google Cloud, catering to both beginners and advanced practitioners. It begins with fundamental concepts, such as creating a GCP account and understanding core cloud services like compute, storage, and analytics, setting a strong foundation for learners new to cloud platforms. A significant portion of this course is dedicated to practical AI services offered by GCP. Learners will gain experience in model creation and deployment using AutoML for various data types—tabular, images, and text. Additionally, there are modules on deploying models via APIs, utilizing the AI Platform through both GUI and coding, and creating pipelines with Kubeflow, which is essential for scalable, production-level ML workflows. The course culminates with a focus on Vertex AI, covering advanced topics such as custom model training, hyperparameter tuning, feature store integration, and pipeline automation, giving learners the tools to develop end-to-end machine learning solutions. **Strengths:** - **Hands-on Approach:** Practical exercises reinforce theoretical concepts, making it easier to grasp complex workflows. - **Comprehensive Coverage:** From cloud basics to advanced ML deployment techniques, the course covers a wide spectrum. - **Real-world Applications:** Designed for those familiar with other cloud platforms like AWS or Azure, providing insights into how ML activities translate onto GCP. - **No Prior GCP Experience Required:** The beginner-friendly start makes it accessible to all levels, with enough depth for experienced practitioners. **Recommendations:** - **Ideal for Cloud and ML Enthusiasts:** If you're looking to leverage GCP for machine learning projects, this course equips you with the necessary skills. - **For Career Growth:** As cloud-based ML solutions are becoming industry standards, this course can add valuable expertise to your portfolio. - **Recommended alongside practical projects:** To fully benefit, supplement the course with personal projects on GCP, experimenting with AutoML, custom training, and pipelines. **Final Verdict:** I highly recommend **"Machine Learning on Google Cloud (Vertex AI) - Hands on!"** for anyone interested in deploying machine learning models at scale on GCP. Its structured, hands-on methodology ensures that you don’t just learn theory but also gain practical skills that can be immediately applied in professional environments. Whether you're transitioning from other platforms or just beginning your cloud ML journey, this course provides a solid, comprehensive foundation. **Enroll now** to start mastering machine learning on one of the world's leading cloud platforms!
Are you a data scientist or AI practitioner who wants to understand cloud platforms? Are you a data scientist or AI practitioner who has worked on Azure or AWS and curious to know how ML activities can be done on GCP?If yes, this course is for you. This course will help you to understand the concepts of the cloud. In the interest of the wider audience, this course is designed for both beginners and advanced AI practitioners.This course starts with providing an overview of the Google Cloud Platform, creating a GCP account, and providing a basic understanding of the platform. Before jumping into the AI services of GCP, this course introduces important services of GCP. Services include Compute, storage, database, IAM, and analytics, followed by a demo of one key component of these services. The last three sections of the course are dedicated to understanding and working on the AI services offered by GCP. You will work on model creation and deployment using AutoML for tabular, images, and text data. Getting predictions from the deployed model using APIs. In the AI platform section, you will work on model creation and deployment using AI Platform (both GUI and coding approach). Creation and submission of jobs and evaluation of the trained model. Pipeline creation using Kubeflow. And in the Vertex AI section, you will work on model creation using AutoML, custom model training, and deployment. Inclusion ofhyperparameter optimization step in the custom model. Kubeflow pipelines creation using AutoML & custom models. You will also work on the Feature store.