AI-Powered Semantic Search & RAG with ElasticSearch and Next.js
Master the art of building intelligent search applications by combining the power of AI-driven semantic search, Retrieval-Augmented Generation (RAG), ElasticSearch for vector storage, and Next.js for a dynamic frontend experience.
AI-Powered Semantic Search & RAG with ElasticSearch and Next.js
Skills you build, step by step.
Practical lessons designed to get you writing working code. Every topic builds directly on the previous one.
Understand the core principles and differences between traditional keyword search and modern semantic search.
Grasp the concept of vector embeddings and their role in representing semantic meaning.
Design and implement a Retrieval-Augmented Generation (RAG) pipeline from scratch.
Utilize Elasticsearch as a high-performance vector store for efficient similarity search.
Integrate large language models (LLMs) to generate contextually relevant and accurate responses.
Who this course is made for.
Clear expectations before you begin. No unnecessary background needed to get moving with confidence.
Target Level
Suitable for advanced learners seeking hands-on build experience.
Prerequisites
- Intermediate knowledge of JavaScript/TypeScript, including asynchronous programming.
- Basic understanding of web development concepts (HTTP, REST APIs, JSON).
- Familiarity with Node.js and npm/yarn for backend development.
- Conceptual understanding of databases and data structures; prior exposure to NoSQL databases is a plus.
- Basic understanding of Machine Learning/AI concepts, particularly Large Language Models (LLMs) and their applications.
What You Need
A computer with an internet connection, a text editor, and time for weekly practice.