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Advanced Agentic AI: Production Data Architecture · LearnSpace
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Advanced Agentic AI: Production Data Architecture

Курс от LearnKartS
Продвинутый≈ 9.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

AI isn’t the future anymore production-ready AI systems are. Are you ready to build them? Most developers learn how to call AI models. But the real advantage lies in building systems that retrieve the right data, process context intelligently, and scale reliably in production. That’s the gap this course closes. In this Agentic AI course, you’ll build a complete RAG pipeline using pgVector and PostgreSQL configuring vector databases, storing embeddings, & executing high-performance similarity search. You’ll design intelligent query pipelines with context construction and prompt engineering to generate precise, grounded outputs. You’ll then integrate RAG with MCP to create AI agents capable of handling real customer and order workflows. Finally, you’ll architect a production-ready MongoDB layer designing schemas, optimizing queries, & migrating services from mock data to scalable systems. What makes this different? You’re not learning isolated tools you’re building a real, end-to-end AI architecture used in modern production environments. Perfect for developers and AI engineers who want to move from experimentation to real impact. Enroll now and stay ahead of the curve.

Навыки, которые вы освоите

MongoDBData MigrationPrompt EngineeringDebuggingPostgreSQLEmbeddingsSystem Design and ImplementationDevelopment EnvironmentData ModelingSQLAgentic WorkflowsContext EngineeringGenerative AI AgentsSystems DesignDatabase DesignData ArchitectureObject-Relational MappingScalability

Программа курса

2 модулей · 53 учебных материалов

01Vector Search & RAG Engine26 материалов

pgVector Configuration and Queries

Course IntroductionВидеоEnabling the pgVector Extension for Database ConfigurationВидеоConnecting NodeJS App to pgVectorВидеоSetting Up PostgreSQL & pgvector ConnectionВидеоCreating the PG Vector Store & Table Schema

Учитесь у экспертов

LearnKartS

Преподаватель курса

Nikhil Agarwal

Преподаватель курса

Advanced Agentic AI: Production Data Architecture
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 9.2 ч

2 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский

Часть программы вашего университета
Видео
Storing Embeddings with SQL UpsertВидео
Building Vector Similarity Search QueriesВидео
Checkpoint QuizЗадание
Proficiency QuizЗадание

RAG Engine Development and Query Processing

Testing the Vector Database IntegrationВидеоCreating the RAG Chunk Interface & RAG Engine ClassВидеоGenerating Query Embeddings & Validating DimensionsВидеоSearching the Vector Database & Processing ResultsВидеоBuilding Context, Prompt Engineering & Final RAG PipelineВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

RAG + MCP Integration

Preparing RAG as a Tool and registering in MCPВидеоPreparing the Environment for Agentic App TestingВидеоTesting Tools and Customer–Order QueriesВидеоDebugging RAG with PGVector and ChromaDBВидеоImproving Prompt Engineering and Final Application TestingВидеоModel Agnostic - Testing Logic with OpenAI GPTВидеоCheckpoint QuizЗаданиеAdvanced Agentic AI Systems: RAG Tool Integration, Testing, Debugging & Model-Agnostic WorkflowsDIALOGUEProficiency QuizЗаданиеTesting, Debugging, and Optimizing a Production-Ready Agentic AI SystemDIALOGUE
02MongoDB Production Architecture27 материалов

MongoDB Architecture Setup

MongoDB Architecture Overview and Integration StrategyВидеоInstalling and Configuring MongoDB Locally on macOSВидеоInstalling and Configuring MongoDB Locally on WindowsВидеоMongoDB Environment Setup & Mongoose InstallationВидеоCreating MongoDB Connection Config & Server InitializationВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

MongoDB Models, Schemas, and Service Migration

Creating Customer Schema & Interface with MongooseВидеоBuilding the Customer Model & Understanding Mongoose ModelsВидеоCreating Order Schema & Preparing Database Insertion ServiceВидеоCreating MCP Tool for Customer Insertion & Testing in Chat AppВидеоMigrating Customer Services from Mock Data to MongoDBВидеоRefactoring Order Services & Understanding Schema + PopulateВидео

Schema Optimization and Advanced MongoDB Handling

Understanding MongoDB _id Issue & Need for Schema OptimizationВидеоCreating Global Schema Options for Cleaner MongoDB ResponsesВидеоApplying Schema Options to Customer Model & Transforming FieldsВидеоImplementing Getters & Date Transformations in Customer SchemaВидеоDesigning Order Schema with References and PopulateВидеоFixing Query Output Types & Optimizing Tool ResponsesВидео
Creating Orders Tool & Testing via Chat ApplicationВидео
Checkpoint QuizЗадание
Advanced Agentic AI Systems: MongoDB Schema Design, MCP Tool Integration & Data Workflow TransformationDIALOGUE
Proficiency QuizЗадание
Building and Integrating Database Schemas with MCP Tools in an Agentic AI SystemDIALOGUE
Checkpoint QuizЗадание
Proficiency QuizЗадание
Course SummaryВидео