Generative AI & LLM – interview notes
Tokens, embeddings, RAG, fine-tuning and hallucinations in short answers.
Tokens, embeddings, RAG, fine-tuning and hallucinations in short answers.
Premium: micro-partitions, clustering, Time Travel, streams and tasks, cost control.
Mean vs median, p-values, A/B tests and correlation vs causation.
Pipelines, containers, blue-green deployments and infrastructure as code.
CIA triad, hashing vs encryption, OWASP Top 10 and zero trust.
Event loop, closures, promises and how browsers render a page.
Dataflow vs Dataproc vs Composer, Pub/Sub delivery guarantees, Beam windowing, CDC with Datastream, Dataplex governance, DR and a full system-design answer.
12 real-world questions on BigQuery internals, partitioning vs clustering, pricing models, storage choices, security and time travel – with model answers.
A practical 6-week plan: the official exam guide, hands-on labs, case-study thinking and the topics I found hardest.
Premium: a layer-by-layer lakehouse design on GCP – landing, raw, curated and serving zones – with the service choices and trade-offs interviewers ask about.
Free one-page revision: storage, processing, orchestration, governance and BI services on Google Cloud, with the one-line reason to pick each.