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Manage Data in Chroma · LearnSpace
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Manage Data in Chroma

Курс от Coursera
Средний≈ 2.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Ready to move beyond basic vector search? This intermediate course is for AI practitioners and developers who want to unlock the full potential of their AI applications by mastering data management in Chroma. You'll learn that the power of a vector database isn't just in finding similar items—it's in finding the right items, precisely and efficiently. This course shows you how to build robust, organized, and scalable Chroma databases from the ground up. You will need to have basic Python programming skills, including familiarity with libraries and data structures like dictionaries. No prior AI/ML experience is required. You will learn to master metadata to create powerful filtering rules that retrieve exactly what you need, and you'll design multi-collection architectures to neatly organize data across different domains, just like real-world systems at companies like IKEA and JPMorgan. Through hands-on labs, you'll move from theory to practice by scripting a complete Python ETL pipeline to ingest, tag, and organize customer support tickets into a clean, queryable, multi-collection Chroma database. By the end of this course, you won't just be using a vector database; you'll be architecting a sophisticated data management engine ready for real-world AI applications.

Навыки, которые вы освоите

Database ManagementData PipelinesData ManagementDocument ManagementData MaintenanceScriptingData ArchitectureLLM ApplicationEmbeddingsData StoreQuery LanguagesMetadata ManagementData Import/ExportVector DatabasesExtract, Transform, Load

Программа курса

3 модулей · 17 учебных материалов

01Foundations: Ingesting and Tagging Data in Chroma6 материалов
The Case for Structured Vector DataDIALOGUEWhat are Documents, Metadata, and Filters in Chroma?ВидеоAnatomy of a Document: Best Practices for MetadataЧтениеAdd a Document with MetadataВидео

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Преподаватель курса

Manage Data in Chroma
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Обучение на Coursera

≈ 2.2 ч

3 модулей

Язык: Английский

Часть программы вашего университета
Hands-On Learning: Ingesting and Tagging DocumentsЛабораторная
Knowledge Check: Metadata and Filtering ConceptsЗадание
02Automation and Scale: Managing Multiple Collections5 материалов
Why Use Multiple Collections? Lessons from Retail and FinanceВидеоDesigning a Multi-Collection ArchitectureЧтениеScripting an Ingestion Pipeline in PythonВидеоDialogue with AI Coach: Planning Your ETL Script for Support TicketsDIALOGUEAutomation and Scale: Managing Multiple CollectionsЗадание
03Advanced Querying and Lifecycle Management6 материалов
The Challenge of a Static DatabaseDIALOGUEMastering the Data Lifecycle: Advanced Querying, Updating, and DeletingЧтениеFull Lifecycle Management with PythonВидео[Ungraded Lab] Hands-On Learning: Maintaining the Customer Ticket DatabaseЧтениеHands-On Learning: Maintaining the Customer Ticket DatabaseЛабораторнаяDynamic Database Management ScriptЗадание