Actually a Nice course for the ones really wanting to understand and implement the security architecture beneath.
ok

Modern AI systems rely on more than traditional ETL pipelines. In this advanced professional certificate, learners build the skills to design, validate, and operate production-grade AI-native data platforms that support machine learning, generative AI, semantic search, and retrieval-augmented generation. The program covers structured and unstructured ingestion, lakehouse architecture, embedding pipelines, vector retrieval systems, reproducible training datasets, CI/CD, governance, observability, and operational reliability. Designed for data engineers and adjacent technical professionals moving into AI platform work, this certificate helps learners move beyond isolated pipelines toward owning reliable, measurable, and governed AI data systems. Through hands-on labs and a portfolio-ready capstone, learners apply architecture and implementation skills to build an end-to-end AI-native data platform, document its tradeoffs, and demonstrate business value. To succeed, learners should already be comfortable with SQL, basic Python, data pipelines, Git, and core software engineering practices.

Actually a Nice course for the ones really wanting to understand and implement the security architecture beneath.
Showing: 3 of 3
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Not able to connect to instructor's explaination. Seems read by some AI instructor
The material in the labs does not appear in the course work.