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3 courses matching “embeddings”

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Abstract cover artwork for RAG Systems in Production, a Agentic AI course Agentic AI
Agentic AI intermediate

RAG Systems in Production

The gap between a RAG demo and a RAG product is chunking strategy, retrieval evaluation and latency budgets. Covers document parsing, chunk boundary design, hybrid retrieval, cross-encoder re-ranking, and caching layers that keep p95 sane.

DO Daniel Okafor 4.9

$89.00

13 hours

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Abstract cover artwork for Recommender Systems from Scratch, a Machine Learning course Machine Learning
Machine Learning intermediate

Recommender Systems from Scratch

Build a recommender end to end: implicit-feedback matrix factorisation, content-based retrieval with embeddings, two-stage retrieve-then-rank architectures, and the cold-start problem every real system faces. Evaluated with offline ranking metrics and an honest discussion of why they disagree with A/B tests.

HT Hiroshi Tanaka 4.9

$89.00

15 hours

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Abstract cover artwork for Vector Databases and Semantic Search at Scale, a Data Engineering course Data Engineering
Data Engineering intermediate

Vector Databases and Semantic Search at Scale

How approximate nearest-neighbour indexes actually work (HNSW, IVF, product quantisation) and what you trade for speed. Metadata filtering, hybrid dense plus sparse retrieval, reciprocal rank fusion, re-indexing strategies for embedding migrations, and keeping a vector store in sync with a relational system of record.

DO Daniel Okafor 4.8

$79.00

10 hours

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