GCP Learning Hub

Role-Based Learning Paths

Curated track sequences for the role you're targeting. Each path lists its focus areas, the ordered tracks, and the outcomes you'll reach.

⚙️

Backend Engineer

Ship production Python & FastAPI services on Google Cloud.

Intermediate ⏱ 8–10 weeks

Track sequence

  1. Cloud & Google Cloud Foundations · 10 hours
  2. Identity & Access Management · 14 hours
  3. Cloud Run & Serverless Containers · 20 hours
  4. Databases · 18 hours
  5. API & Backend Engineering · 20 hours
  6. Event-Driven Architecture · 16 hours
  7. Observability & Operations · 15 hours
  8. Infrastructure as Code · 16 hours

You'll be able to

  • Deploy an authenticated FastAPI service to Cloud Run with a private AlloyDB connection
  • Design idempotent, traceable APIs with background processing
  • Automate deployment with Terraform and structured logging

Focus areas

PythonFastAPICloud RunCompute EngineAPI GatewayApigee fundamentalsCloud SQLAlloyDBFirestoreMemorystorePub/SubCloud TasksSecret ManagerCloud LoggingCloud TraceTerraform
☁️

Cloud Engineer

Design, secure, and operate Google Cloud infrastructure.

Intermediate ⏱ 10–12 weeks

Track sequence

  1. Cloud & Google Cloud Foundations · 10 hours
  2. Resource Hierarchy & Governance · 9 hours
  3. Identity & Access Management · 14 hours
  4. Networking · 18 hours
  5. Compute Engine · 13 hours
  6. Cloud Run & Serverless Containers · 20 hours
  7. Storage · 10 hours
  8. Observability & Operations · 15 hours
  9. Reliability & Disaster Recovery · 15 hours
  10. Cost Optimization & FinOps · 12 hours

You'll be able to

  • Stand up a Shared VPC landing zone with least-privilege IAM
  • Design multi-zone, private-networked workloads
  • Operate with SLOs, budgets, and disaster-recovery plans

Focus areas

Resource hierarchyIAMVPCCloud Load BalancingCloud DNSCloud NATPrivate Service ConnectCompute EngineCloud RunGKECloud StorageMonitoringSecurityReliabilityCost management
🔁

DevOps & Platform Engineer

Build golden paths, pipelines, and platform automation.

Advanced ⏱ 10–12 weeks

Track sequence

  1. Identity & Access Management · 14 hours
  2. Networking · 18 hours
  3. Infrastructure as Code · 16 hours
  4. DevOps & CI/CD · 17 hours
  5. Cloud Run & Serverless Containers · 20 hours
  6. Google Kubernetes Engine · 22 hours
  7. Observability & Operations · 15 hours
  8. Security Engineering · 18 hours

You'll be able to

  • Build a keyless GitHub Actions → Cloud Run pipeline with Workload Identity Federation
  • Ship canary and blue-green deployments with Cloud Deploy
  • Enforce policy and supply-chain security across environments

Focus areas

Artifact RegistryCloud BuildCloud DeployGitHub ActionsTerraformGKECloud RunConfig managementSecret managementObservabilityPolicy enforcementMulti-environment deploymentsPlatform automation
🔧

Data Engineer

Build batch and streaming data platforms on GCP.

Advanced ⏱ 10–12 weeks

Track sequence

  1. Cloud & Google Cloud Foundations · 10 hours
  2. Storage · 10 hours
  3. Event-Driven Architecture · 16 hours
  4. Data Engineering · 22 hours
  5. Analytics & BigQuery · 16 hours
  6. Workflow Orchestration · 15 hours
  7. Observability & Operations · 15 hours
  8. Cost Optimization & FinOps · 12 hours

You'll be able to

  • Build a streaming Pub/Sub → Dataflow → BigQuery pipeline with dead-letter handling
  • Design partitioned, clustered warehouses that control query cost
  • Orchestrate pipelines with Composer and enforce data quality

Focus areas

Cloud StorageBigQueryPub/SubDataflowDataprocCloud ComposerDatastreamDataformData lake architectureStreaming pipelinesData governanceData qualityCost optimization
🤖

AI & Machine Learning Engineer

Train, deploy, and monitor models on Vertex AI.

Advanced ⏱ 10–12 weeks

Track sequence

  1. Cloud & Google Cloud Foundations · 10 hours
  2. Storage · 10 hours
  3. Analytics & BigQuery · 16 hours
  4. Machine Learning on Vertex AI · 20 hours
  5. MLOps & LLMOps · 16 hours
  6. Observability & Operations · 15 hours
  7. Cost Optimization & FinOps · 12 hours

You'll be able to

  • Train custom models and serve them from Vertex AI endpoints
  • Build Vertex AI Pipelines with a Model Registry and monitoring
  • Automate retraining with an end-to-end MLOps platform

Focus areas

Vertex AIWorkbenchPipelinesTrainingPrediction endpointsModel RegistryFeature managementExperiment trackingModel evaluationModel monitoringBigQuery MLData preparationMLOps
✨

Generative AI Engineer

Build production RAG, agents, and LLM platforms.

Advanced ⏱ 12–14 weeks

Track sequence

  1. API & Backend Engineering · 20 hours
  2. Cloud Run & Serverless Containers · 20 hours
  3. Databases · 18 hours
  4. Generative AI on Vertex AI · 24 hours
  5. Production RAG on GCP · 26 hours
  6. AI Agents & Multi-Agent Systems · 22 hours
  7. LLM Gateway & Model Routing · 14 hours
  8. Observability & Operations · 15 hours
  9. Cost Optimization & FinOps · 12 hours

You'll be able to

  • Build a grounded, cited RAG API on Cloud Run with hybrid retrieval
  • Orchestrate multi-agent workflows with evaluation and guardrails
  • Operate an LLM gateway with routing, fallback, and semantic caching

Focus areas

Vertex AIModel GardenGemini APIsPrompt engineeringStructured outputFunction callingMultimodalEmbeddingsVector searchRAG EngineAlloyDB AIVertex AI Vector SearchAgent BuilderAgent EngineADKEvaluationGuardrailsLLM observabilityCost optimization
🏗️

Cloud Solutions Architect

Turn requirements into secure, reliable, cost-aware designs.

Advanced ⏱ 12–14 weeks

Track sequence

  1. Cloud & Google Cloud Foundations · 10 hours
  2. Resource Hierarchy & Governance · 9 hours
  3. Networking · 18 hours
  4. Cloud Run & Serverless Containers · 20 hours
  5. Databases · 18 hours
  6. Security Engineering · 18 hours
  7. Reliability & Disaster Recovery · 15 hours
  8. Google Cloud Architecture · 18 hours
  9. Cost Optimization & FinOps · 12 hours
  10. Google Cloud Interview Preparation · 16 hours

You'll be able to

  • Produce a defensible multi-region architecture with an explicit DR strategy
  • Justify every service selection against access patterns and cost
  • Communicate architecture decisions clearly in senior interviews

Focus areas

Requirement analysisService selectionCapacity estimationNetworkingSecurityReliabilityMulti-region systemsDisaster recoveryData architectureIntegration patternsObservabilityCost optimizationArchitecture communication