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Know Thyself - The Value and Limits of Self-Knowledge: The Examined Life
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Secure and operate production GKE clusters: Kubernetes RBAC, Workload Identity, Pod security, Cloud Logging and Monitoring, Cloud Storage and Cloud SQL integration, and CI/CD with Cloud Deploy.
Deploy and manage Google Cloud core services: IAM roles and service accounts, Cloud Storage buckets with encryption, Cloud SQL, billing quotas, and monitoring with Cloud Observability.
Deploy Google Cloud infrastructure with Compute Engine: configure VPC networks, subnetworks, IP addresses, routes and firewall rules, and create virtual machines using the Console and Cloud Shell.
Configure HA VPN, Cloud Interconnect and peering, application and internal load balancers with autoscaling, and automate Google Cloud infrastructure deployment with Terraform.
Learn to frame machine learning problems, follow the five phases on the path to ML, train AutoML image and video models on Vertex AI, and spot data bias.
Compare Google Cloud computing and storage services through hands-on labs: Compute Engine, VPC networking, Cloud Storage, Cloud SQL, Kubernetes Engine, Cloud Run, IAM and billing.
Translate business problems into machine learning use cases, assess feasibility, evaluate model fairness, and run labs with Vertex AutoML Vision, Natural Language API, and BigQuery ML.
Coordinate microservices with orchestration and choreography: build event-driven applications on Google Cloud using Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler.
This course helps learners create a study plan for the PCA (Professional Cloud Architect) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual stud…
Build no-code apps with AppSheet: connect spreadsheet data sources, structure multiple tables, design views for the user experience, and deploy the app to end users.
Explore data in Looker without SQL: work with dimensions, measures and filters, write table calculations and offsets, and build, share and schedule Looks and dashboards.
Deploy cloud-native applications on Google Cloud: build pipelines with Cloud Build and Terraform, deploy to Kubernetes Engine, compare compute options, and troubleshoot with Cloud Trace and Cloud Monitoring.
Pull BigQuery data into Google Sheets with Connected Sheets, prime and filter it, run the analysis, then visualize and share insights with decision makers.
Build code-free ETL and realtime pipelines with Cloud Data Fusion, then share data securely across a lakehouse using BigQuery, Analytics Hub, and Dataplex.
Secure public sector workloads on Google Cloud: apply BeyondCorp zero trust and IAP, mitigate DDoS with Cloud Armor, and meet compliance using Assured Controls.
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