Data Engineering for AI: Pipelines, Vector Stores and Data Quality

A premium, advanced course on the data foundation that every serious AI system depends on, updated for 2026. This is not a retrieval-and-generation (RAG) course - it is the data engineering underneath: how raw data becomes trustworthy fuel for LLMs, agents and vector search. You will master batch versus streaming paradigms, real-time ingestion with Kafka and Flink, ETL/ELT and orchestration with Apache Airflow, Dagster and dbt, lakehouse architecture with Parquet and Apache Iceberg, ingestion from diverse sources with change data capture and schema evolution, data quality and validation with Great Expectations, data contracts and governance, testing and CI/CD for pipelines (DataOps), chunking and preprocessing for LLM pipelines, feature stores for ML and AI workloads, embeddings pipelines at scale, and vector databases in depth (pgvector, Pinecone, Qdrant, Weaviate) including HNSW and IVF index internals, hybrid search, sharding and metadata filtering. It closes with retrieval quality evaluation, metadata and lineage, PII detection and anonymization, GDPR-compliant pipelines, cost and performance engineering, pipeline monitoring, and a comprehensive final assessment. Real Python and SQL throughout.

The course has 10 modules and 31 lessons, with 390 quiz questions. The full curriculum, module by module, is shown on the course page.

Yes. The course is Advanced level and assumes hands-on experience with AI in its field.

The estimated duration is about 26 hours, across 31 lessons. You learn at your own pace, and your progress is saved automatically at every lesson, so you can pick up where you left off.

Access to this course alone costs €99 per month. The course is also included in the IT Pro bundle, €399 per month for all 25 IT Pro courses, and in All Access, €499 per month for the whole international catalog.

Plans are billed monthly, in EUR. Every price is a total, with VAT included at the rate of your country. Compare the plans.

Yes. You can read a free preview of lesson 1, “The Role of Data Engineering in AI in 2026”, without an account. The preview shows you how the lesson is written; the rest of the lesson and the other lessons open after payment.

The AI Professor is built into every lesson and starts from the lesson you have open: it explains the passages you select, gives you examples, summarizes the lesson, tests you with a quiz and prepares review flashcards. You can type or talk to it, in English.

It is included in your subscription, per-course access included, with a monthly fair-use limit. It is an AI system, not a human teacher, and its answers may contain errors; details in the Terms.

When you meet the completion thresholds shown on the platform (lessons completed and the minimum quiz score), you can issue your Certificate of Completion for “Data Engineering for AI: Pipelines, Vector Stores and Data Quality” from your account, with a unique number, publicly verifiable on the site.

It is a private attestation of course completion, issued by GALIAN SOFTWARE DEVELOPMENT SRL. It is NOT a diploma or a state-recognised qualification under Romanian Laws 198/2023, 199/2023 or Government Ordinance 129/2000; employers may take it into account at their own discretion. Details in the Certification policy.

Yes. Course access and the bundles are subscriptions that renew automatically at the end of each monthly billing period. You can see the next renewal date in your account at any time.

You can stop the renewal at any time, from your account or by email, with no other formality. Access stays active until the end of the period already paid for, and no pro-rata refund is made for a period already started, except in the cases provided by law. Your progress stays saved in your account. Details in the Terms & Conditions, section 5.5.

Yes. Company plans give a team access to the courses, with a dashboard where you follow each member’s progress and manage seats centrally. See the plans for companies.