Pinecone: Data modelling
Apply Pinecone through entities, relationships, constraints.
Advanced / Structured learning draft / Version 0.9
Structured learning draftVector Databases for AI Apps
Model, query and explain dependable data. You will finish with a working data model with validated queries.
This open learning manuscript is undergoing course-specific editorial review. It does not provide certification. Progress and notes are stored only in this browser.
DatabasesTool stack
PostgreSQLLangChain
12guided lessons
4focused modules
1reviewable project
PDFoffline workbook
The problem
What this course helps you do
Vector Databases for AI Apps is a structured, practical course covering Pinecone, Weaviate, pgvector, RAG, Embeddings. It emphasizes explainable methods, checked work and a final outcome that can be reviewed.
Who it is for
Developers and analysts who need dependable data systems.
Prerequisites
- Basic programming or spreadsheet experience
Portfolio-ready project
Produce a reviewable Vector Databases for AI Apps project using Pinecone, Weaviate, pgvector.
Deliverable: A working Vector Databases for AI Apps artefact plus an evidence-based self-review.
Practice fileRelational data practiceSafe SQL schema and queries for a fictional service business.Planning template · MarkdownProject briefDefine the user, outcome, boundaries, evidence and acceptance criteria before building.Printable workbook · PDFComplete course workbookA4-ready lesson prompts, project worksheets, evidence logs and references.
Downloads open without an account. Practice data is fictional; review each file before using it in another system.
Definition of done
- The output matches the stated outcome.
- Inputs and decisions are reproducible.
- Boundary and failure evidence is included.
- Limitations and responsibility considerations are explicit.
Course plan
From first concept to finished work
Weaviate: Querying
Apply Weaviate through selection, joins, aggregation.
pgvector: Reliability
Apply pgvector through transactions, indexes, backups.
RAG: Production design
Apply RAG through security, performance, operations.
Source-led learning
Authoritative references
Course claims are grounded in primary documentation and recognized public guidance. Recheck version-sensitive information before professional use.
- PostgreSQL TutorialPostgreSQL Global Development Group
- SQL LanguagePostgreSQL Global Development Group