On-demand activities
Google Cloud 根據您的需求規劃了全方位的課程內容，內含超過 980 項學習活動，並涵蓋多種活動型態，您可自由選擇。您可以選擇簡短的個別研究室，或是包含影片、文件、研究室和測驗的多單元課程。在研究室中，您可以透過臨時憑證實際使用雲端資源，直接累積 Google Cloud 實作經驗。完成課程可獲得徽章，讓您輕鬆掌握、追蹤及評估自己的 Google Cloud 學習成果！
-
课程 精选 API Design and Fundamentals of Google Cloud's Apigee API Platform
In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API life cycle, and how the Apigee API platform helps you manage all aspects of the life cycle. You learn about how APIs can be designed using API proxies, and how APIs are packaged as API prod…
-
课程 精选 Managing and Securing the Apigee Hybrid API Platform
This course discusses how environments are managed in Apigee hybrid, and how runtime plane components are secured. You will also learn how to deploy and debug API proxies in Apigee hybrid, and about capacity planning and scaling.
-
课程 精选 Computer Vision Fundamentals with Google Cloud
This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear mod…
-
课程 精选 Recommendation Systems on Google Cloud
In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.
-
课程 精选 Networking in Google Cloud: Fundamentals
Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals. This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharin…
-
课程 精选 Launching into Machine Learning
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a …
-
课程 精选 TensorFlow on Google Cloud
This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.
-
课程 精选 Machine Learning in the Enterprise
This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three…
-
课程 精选 Smart Analytics, Machine Learning, and AI on Google Cloud
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course…
-
课程 精选 Mitigating Security Vulnerabilities on Google Cloud
In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud log…