Johnfar Kerlee
Member since 2019
Bronze League
1200 points
Member since 2019
The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.
In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.
In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
如果您是剛起步的雲端開發人員, 想在 Google Cloud Essentials 外獲得更多實作經驗,歡迎參加本課程。您將透過實作實驗室, 深入瞭解 Cloud Storage 和其他重要應用程式服務,例如: Monitoring 和 Cloud Functions。您將習得 在任何 Google Cloud 專案都適用的寶貴技能。
TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
在這堂入門課程,您將實際練習使用 Google Cloud 的基礎工具和服務。本課程包含可選擇觀賞的影片, 針對實驗室涵蓋的概念提供更多背景資訊,協助您複習。「Google Cloud 必備知識」 是適合 Google Cloud 學員的第一堂課, 即使您尚未學習或不熟悉雲端知識, 也能從這堂課獲得實務經驗,並應用於第一項 Google Cloud 專案。不管是撰寫 Cloud Shell 指令 和部署第一部虛擬機器,還是在 Kubernetes Engine 或透過負載平衡執行應用程式, 「Google Cloud 必備知識」都是認識平台基本功能的最佳入門資源。
大數據、機器學習和人工智慧 (AI) 是時下熱門的 電腦相關話題,但這些領域相當專業,就算想要入門 也難以取得教材或資料。幸好,Google Cloud 提供了此領域的多種服務,而且容易使用。 參加這堂入門課程,您就能踏出第一步, 開始學習運用 BigQuery、Cloud Speech API 以及 Video Intelligence 等工具。
Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.