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Learn how Dataflow runs Apache Beam pipelines: Beam portability and Runner v2, Shuffle Service and Streaming Engine, IAM and quotas, and security with Private IPs and CMEK.
Develop Dataflow pipelines with the Beam SDK: windows, watermarks and triggers, sources and sinks, schemas, State and Timer APIs, Beam SQL, DataFrames and notebooks.
Monitor, troubleshoot, and tune Dataflow pipelines with job metrics, logging, and error reporting, then apply testing, CI/CD, reliability practices, and classic and Flex Templates.
Navigate Google Drive to upload, organize, and share files: assign collaborator roles, create shared drives, use templates, work offline with Drive File Stream, and add Marketplace apps.
Create and run video conferences in Google Meet: schedule and join meetings, manage layouts and chat, use Companion Mode, host controls, recording, and live streaming.
Create presentations in Google Slides: apply themes and layouts, insert tables, images and charts, add transitions and animations, share, collaborate with comments, and present.
Build LookML data models in Looker: define dimensions and measures, model Explores with filters, and create SQL, native, and persistent derived tables with datagroup caching.
Store data in Google Cloud: use Cloud Storage, Cloud SQL, Spanner, Firestore and Bigtable, publish messages with Pub/Sub, and control access with IAM.
Build secure Google Cloud networks with VPCs, IP addressing, routes and firewall rules, load balancing with Cloud Armor, then monitor infrastructure using Google Cloud Observability and Terraform.
Work with Google Cloud's big data and ML services: run Managed Service for Apache Spark jobs, build Dataflow ETL pipelines, query BigQuery, and call pre-built AI APIs.
Build a loosely coupled Java microservices application with Spring Boot and Spring Cloud on Google Cloud, including retrieving credentials from Secret Manager.
Learn Google's SRE practices: blameless postmortems, SLOs with error budgets, reducing toil, canarying, and how leaders drive organizational adoption and team maturity.
Modernization is more than moving to the cloud: compare SAP deployment options on Google Cloud, unify enterprise data, and build agentic solutions with best practices.
Build production ML pipelines with TFX components and orchestration, add CI/CD and ML metadata, and run continuous training with Kubeflow, Cloud Composer, and MLflow.
Design, deploy, and scale containerized applications on Cloud Run: build images with Docker and Buildpacks, manage traffic, IAM least privilege, load balancing, Cloud SQL, and Pub/Sub.
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