Google Cloud Professional Architect: Get Certified 2022
What you'll learn
- Focus on the latest exam and in depth analysis of case studies
- Learn some of the most demand skills: Kubernetes, Cloud SQL, BigQuery, IAM
- Understand Hybrid Cloud, VPNs, Cloud Interconnect, and service-centric networking
- Know when to use Compute Engine, Kubernetes, Cloud Functions, App Engine and Cloud Run
- Understand how and when to use Cloud Storage, Cloud SQL, BigQuery, Bigtable and Memorystore
- Know how to design resilient and scalable pipelines with Cloud Pub/Sub and Cloud Dataflow
- Migrate workloads and data to the cloud
- Modernize applications with containers and Kubernetes
Requirements
- Understand the basics of cloud computing
- Have some familiarity with networking
- Have some familiarity with software engineering
Description
Get started in one of the most challenging and rewarding careers, cloud architecture. Cloud architects are in high demand and they are some of the top paid certified professionals.
Architects must have broad technical knowledge spanning compute, storage, networking, data analysis, software engineering, security, and DevOps. And that's not all -- architects must know how to work with sponsors, end users, and subject matter experts to define requirements and create a technical framework for developers, network engineers, data modelers, and other technical experts.
This course is designed and developed by the author of the official Google Cloud Professional Architect exam guide and an architect with decades of experience in systems design, software engineering, data architecture and machine learning. This course combines lectures with quizzes to ensure you understand the full breadth of the Google Cloud Professional Architect exam, including:
Compute services including Compute Engine, App Engine, Kubernetes Engine, and Cloud Functions
Storage services like Cloud Storage, Cloud SQL, Cloud Spanner, Firestore, Bigtable, BigQuery
Data pipeline and analytic services, such as Cloud Dataflow, Cloud Data Fusion, Cloud Datproc, and Vertex AI
Networking services from Cloud Router and Cloud NAT to Private Service Connect and Data Loss Prevention Service
Migrating to the cloud and migration strategies
Security, from access controls and policies to regulations and compliance
This course is designed to not only help you pass the Google Cloud Professional Architect exam but too also succeed as an architect. Learn how to think through architecture challenges, assess various options, balance business, and technical requirements, and deliver highly scalable, reliable, and efficient systems.
The course includes a 50 question practice exam that will test your knowledge of data engineering concepts and help you identify areas you may need to study more.
By the end of this course, you will be ready to use Google Cloud services to design, deploy and monitor applications, deploy advanced data management systems, design networks to support hybrid computing, ensure streamlined operations in the cloud, migrate workloads to the cloud, and much more.
ARE YOU READY TO THINK LIKE AN ARCHITECT AND PASS GOOGLE CLOUD PROFESSIONAL ARCHITECT EXAM? LET'S GET STARTED.
Who this course is for:
- You are interested in getting started in cloud
- You want to become a Google Cloud Professional Architect
- You are an architect interested in learning about cloud
- Software engineers, DevOps engineers,
- You want to become Google Cloud Certified Digital Leader
Instructor
![Dan Sullivan](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.5 Instructor Rating
- 17,873 Reviews
- 144,307 Students
- 12 Courses
Dan Sullivan is a cloud architect, systems developer, and author of the Official Google Cloud Professional Architect Study Guide, the Official Google Cloud Professional Data Engineer Study Guide, and the Official Google Cloud Associate Engineer Study Guide.
He is an experienced trainer and his online training courses have been viewed over 1 million times. Dan has extensive experience in multiple fields, including cloud architecture, data architecture and modeling, machine learning, data science, and streaming analytics.