The Google Kubernetes Engine Architecture specialty will teach you how to use Google Kubernetes Engine (GKE) to develop solutions, such as authoring, programming, load balancing, and monitoring workloads, as well as offering service discovery, role-based access control, and security. for those applications, as well as offering persistent storage, which is one of the Best Online Google App Engine Courses. These hands-on components allow you to put what you've learned in the video sessions into practice. Topics such as Google Cloud Platform products utilized and configured in Qwiklabs will be covered in projects. You may expect to acquire practical experience with the principles covered in the modules.

This course covers the vocabulary and ideas you'll need to get started with Google Cloud Platform (GCP). You'll learn about Google Cloud Platform's compute and storage services, including Google App Engine, Google Compute Engine, Google Kubernetes Engine, Google Cloud Storage, Google Cloud SQL, and BigQuery, as well as how to compare them. You'll learn about the Google Cloud Resource Manager hierarchy and Google Cloud Identity and Access Administration, as well as other critical resource and policy management tools. Basic skills for dealing with GCP are taught in hands-on laboratories.

What you will learn:

• Understand the difference between Google Cloud compute platforms
• Understand Kubernetes components and architecture
• Store container images in Container Registry
• Configure Identity and Access Management Roles for GKE and Set Security Policies for Kubernetes Pods

This course offers:

• Shareable certificate: Get a Certificate when you complete
• 100% online courses
• Planning flexible
• Beginner level
• Approximately 2 months to complete (Recommended pace of 7 hours/week)
• Subtitles: Portuguese (Brazilian), English

Rating: 4.9/5

Enroll here: https://www.coursera.org/specializations/architecting-google-kubernetes-engine-br

This program will provide you with the skills you need to improve your career in cloud architecture, as well as a road to earning the Google Cloud Professional Cloud Architect certification, which is well recognized in the industry. You'll implement solution parts such as infrastructure components including networks, systems, and application services, and you'll earn real-world experience through hands-on Qwiklabs projects that you can show potential employers.

You'll also get the chance to put your case analysis, identify technical watchpoints, and generate potential solutions into reality. Activity Tracking Challenge Labs will put your fundamental talents to the test. This program will give learners seeking certification with example questions identical to those on the test, as well as solutions and practice exam quizzes that imitate the exam-taking experience.

You will get a certificate of accomplishment upon successful completion of this program, which you may share with your professional network and future employers. You must register for and pass the certification test if you want to achieve your Google Cloud certification. Please note that while this program will help you gain the abilities you need to pass the certification test, the certification exam and fee are not included in the training program's cost.

What you will learn:

• Learn the skills needed to be successful in a cloud architect role
• Prepare for the Professional Cloud Architect certification
• Learn about the infrastructure and platform services provided by Google Cloud Platform
• Identify the purpose and value of Google Cloud products and services.

This course offers:

• Shareable certificate: Get a Certificate when you complete
• 100% online courses
• Flexible schedule
• Intermediate level
• Approximately 5 months to complete (Recommended pace of 3 hours/week)
• Subtitles: English, French, German, Russian, Spanish, Japanese

Rating: 4.8/5

Enroll here: https://www.coursera.org/professional-certificates/gcp-cloud-architect

Number of Preparation for Google Cloud Certification: Cloud Devops Professional Certificate Engineer is one of the Best Online Google App Engine Courses. This program will teach you the skills you'll need to enhance your career as a data engineer, as well as prepare you for the industry-recognized Google Cloud Professional DevOps Engineer certification. 87 percent of Google Cloud certified users say their cloud abilities have improved.

You'll also get hands-on experience building software delivery pipelines, deploying and monitoring services, and managing and learning from problems using Google Cloud. Among other things, you'll learn how to apply SRE concepts to a service, as well as approaches for monitoring, debugging, and enhancing infrastructure and application performance. Your path to Google Cloud certification includes the following steps:

1. Earn the Coursera Professional Certificate in Site Reliability Engineering and DevOps.
2. For the Google Cloud Professional Cloud DevOps Engineer certification test, review additional suggested study materials.
3. Study the test guide for Professional Cloud DevOps engineers.
4. Practice for the Professional Cloud DevOps Engineer test.
5. Make an appointment to take the Google Cloud certification exam (Which can be taken remotely or at a test center)

What you will learn:

• Learn the skills needed to be successful in a cloud devops engineering role
• Prepare for the Google Cloud Professional Cloud DevOps Engineer certification exam
• Techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud are guided by the principles of SRE.
• Understand the purpose and intent of the Professional Cloud DevOps Engineer certification and its relationship to other Google Cloud certifications

This course offers:

• Shareable certificate: Get a Certificate when you complete
• 100% online courses
• Planning flexible
• Beginner level
• Approximately 5 months to complete (Recommended pace of 3 hours/week)
• Subtitles: English, French, German, Russian, Spanish, Japanese

Rating: 4.8/5

Enroll here: https://www.coursera.org/professional-certificates/sre-devops-engineer-google-cloud

87 percent of Google Cloud certified users say their cloud abilities have improved*. This program gives you the skills you'll need to develop your security engineering career, as well as training to help you prepare for the industry-recognized Google Cloud Professional Cloud Security Engineer certification.

You'll also have the option of configuring access, network security, and data protection, among other things. Your path to Google Cloud certification includes the following steps:

1. Earn the Google Cloud Security Professional Certificate through Coursera.
2. For the Google Cloud Professional Cloud Security Engineer test, review additional suggested study materials.
3. Go over the test guide for the Google Cloud Professional Security Engineer.
4. Review the sample questions for Professional Cloud Security Engineer.
5. Make an appointment to take the Google Cloud certification exam. (You may take the exam online or at a testing facility.)

Learners will build, edit, remove, and undelete custom IAM roles, just like they would for Google Cloud access components. They'll employ network peering to allow internal IP addresses to be shared across two VPC networks. In Google Cloud, students will design and setup a private Kubernetes cluster. The Kubernetes nodes will run on virtual computers that will not be accessible from the outside world. They'll implement fine-grained limitations to intra-cluster communication using network regulations. Finally, they'll set up two service accounts for two user personas, as well as namespaces for development, testing, and production (ie, development, testing, and production). Learners will also undertake some basic debugging and set API rights for a cluster application.

This course offers:

• Shareable certificate: Get a Certificate when you complete
• 100% online courses
• Flexible schedule
• Intermediate level
• Approximately 9 months to complete (Recommended pace of 2 hours/week)
• Subtitles: English, French, German, Russian, Spanish, Japanese, Portuguese (Brazilian)

Rating: 4.8/5

Enroll here: https://www.coursera.org/professional-certificates/google-cloud-security

Many conventional businesses rely on outdated systems and applications that fail to expand and respond quickly enough to satisfy new client demands. Business executives and IT decision-makers are continuously faced with the option of whether to maintain old systems or invest in cutting-edge new goods and services. Infrastructure and Application Modernization with Google Cloud is one of the Best Online Google App Engine Courses.

This course examines the issues of an out-of-date IT infrastructure and how organizations might use cloud technologies to update it. It begins by examining the various cloud compute solutions and their benefits before moving on to application modernization and Application Programming Interfaces (APIs). The course also covers a variety of Google Cloud products, such as Compute Engine, App Engine, and Apigee, that may assist organizations in better developing and managing their systems.

This course can be applied to a variety of Professional Certificate or Specialization programs. This course will credit toward your training in one of the following programs if you finish it successfully:

• Number of Google Cloud Digital Leader Professional Certificate Training
• Digital Transformation Specialization Using AI/ML with Google Cloud

What you will learn:

• Describe the key benefits of infrastructure and app modernization with reference to cloud technology.
• Differentiate between virtual machines, containers, and Kubernetes.
• Explain the Google Cloud solutions that help businesses to better manage their systems, such as App Engine and Google Kubernetes Engine.
• Explain how Google Cloud solutions support app modernization and simplify API management.

This course offers:

• Flexible deadlines
• Shareable certificate: Get a Certificate when you complete
• 100% online
• Beginner level
• Approx. 2 hours to complete
• Subtitles: English
  

Rating: 4.8/5
Enroll here: https://www.coursera.org/learn/google-cloud-product-fundamentals

Application developers learn how to design, create, and deploy apps that seamlessly incorporate Google Cloud managed services in this specialty. Participants will learn how to utilize Google Cloud services and pre-trained machine learning APIs to construct safe, scalable, and intelligent cloud-native apps through a combination of talks, demos, and hands-on labs. Learners can complete labs in Node.js, Java, or Python, depending on their preferences.

One of the Best Online Google App Engine Courses is Developing Applications with Google Cloud Specialization. This course is for application developers who wish to create cloud-native applications or rewrite existing apps to operate on Google Cloud. The following abilities are taught in this course:

• When developing an application, use best practices.
• For application data, select the appropriate data storage choice.
• Make federated identity management a reality.
• Create microservices or loosely linked application components.
• Connect data sources and application components.
• Troubleshoot, trace, and monitor your apps.
• Use containers and deployment services to create repeatable deployments.
• Select the right application runtime environment; for example, utilize Google Kubernetes Engine as a runtime environment and then transition to a no-ops solution using Google App Engine flexible environment.

What you will learn:

• Identify the purpose and value of Google Cloud products and services
• Describe best practices for cloud-native application development
• Implement federated identity management using Firebase authentication
• Deploy applications using Container Builder, Container Registry, and Terraform

This course offers:

• Shareable certificate: Get a Certificate when you complete
• 100% online courses
• Flexible schedule
• Intermediate level
• Approximately 5 months to complete (Recommended pace of 3 hours/week)
• Subtitles: English, French, German, Russian, Spanish, Japanese

Rating: 4.7/5

Enroll here: https://www.coursera.org/specializations/developing-apps-gcp

Building machine learning models with Python and a machine learning framework is the first step toward constructing an enterprise-grade ML architecture, but there are still two major challenges to overcome: training the model with enough computing power to produce the best possible model and then making that model available to users who aren't data scientists or even Python users. Architecting Production-Ready Machine Learning Models is the title of this course. You'll learn how to do on-cloud distributed training and hyperparameter tweaking using the Google Cloud ML Engine, as well as how to make your ML models available for use in prediction via simple HTTP queries.

First, you'll learn how to use the ML Engine with XGBoost models. XGBoost is a machine learning framework that uses the Ensemble Learning approach to create a single, strong model by merging numerous weak learners. Then you'll see how simple it is to migrate serialized models from on-premise to GCP. You'll create a basic model in scikit-learn, the most popular traditional machine learning framework, and then serialize and upload it to the GCP using the ML Engine. Finally, you'll learn how to use TensorFlow, one of the most popular libraries for deep learning applications, to harness the full potential of distributed training, hyperparameter tweaking, and prediction.

You'll learn how the TF CONFIG JSON environment variable is utilized to convey state information and improve the training and hyperparameter tuning process. After completing this course, you'll have the skills and understanding of the Google Cloud ML Engine required to reap the full benefits of distributed training and make batch and online prediction available to your client apps via simple HTTP queries.

Table of contents:

• Course Overview
• Introducing the Google Cloud ML Engine
• Deploying XGBoost Models to the Cloud ML Engine
• Deploying Scikit-learn Models to the Cloud ML Engine
• Deploying TensorFlow Models to the Cloud ML Engine

Level: Intermediate

Enroll here: https://www.pluralsight.com/courses/google-ml-engine-architecting-production-ready-models