Master Google Cloud Through Real-World Engineering
Learn Google Cloud by building production-grade APIs, event-driven systems, data platforms, RAG pipelines, AI agents, and scalable cloud architectures.
Your GCP Learning Progress
Tracked locally on this device. Mark topics complete as you go — scores update live.
Start with a high-impact track
31 tracks span foundations to production RAG and multi-agent systems. Here are a few learners reach for first.
Identity & Access Management
Principals, roles, policies, conditional & deny policies, Workload Identity Federation, and least privilege.
Networking
VPC, subnets, firewall policies, Cloud NAT, load balancing, Private Service Connect, and zero-trust networking.
Cloud Run & Serverless Containers
Services, Jobs, concurrency, cold starts, VPC egress, service-to-service auth, and deploying FastAPI to production.
Databases
Cloud SQL, AlloyDB (+ AI/vector), Firestore, Bigtable, Spanner, and Memorystore — with a selection framework.
Generative AI on Vertex AI
Model Garden, Gemini APIs, prompting, structured output, function calling, embeddings, safety, and eval.
Production RAG on GCP
Ingestion, chunking, embeddings, hybrid retrieval, reranking, grounding, eval, and 18 architecture patterns.
Or follow a role-based path
Curated sequences that take you from where you are to interview- and production-ready.
Backend Engineer
Ship production Python & FastAPI services on Google Cloud.
Cloud Engineer
Design, secure, and operate Google Cloud infrastructure.
DevOps & Platform Engineer
Build golden paths, pipelines, and platform automation.
Data Engineer
Build batch and streaming data platforms on GCP.
AI & Machine Learning Engineer
Train, deploy, and monitor models on Vertex AI.
Generative AI Engineer
Build production RAG, agents, and LLM platforms.
Cloud Solutions Architect
Turn requirements into secure, reliable, cost-aware designs.
What you'll be able to do
Design cloud architectures
Requirement analysis, service selection, multi-region, and DR — then explain them in interviews.
Deploy Python & FastAPI
Ten deployment paths across Cloud Run, GKE, and Compute Engine with auth, tracing, and private networking.
Build event-driven systems
Pub/Sub, Eventarc, Cloud Tasks, dead-letter topics, idempotency, and fan-out.
Process long-running jobs
Async job APIs, state tables, Cloud Run Jobs, Batch, and checkpointing.
Build production RAG
Ingestion, hybrid retrieval, reranking, grounding, citations, and evaluation.
Orchestrate AI agents
Tool calling, Agent Engine / ADK, guardrails, and multi-agent workflows.
Secure cloud resources
Least privilege, Workload Identity Federation, VPC-SC, KMS, and zero-trust.
Control cloud costs
Unit economics, FinOps, and configurable cost calculators for every service.