Vector Database Course in Chennai

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25 hrs of E-Learning Videos
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Vector Database Course Overview

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Upcoming Vector Database Batches

21-09-2026
Mon-FriWeekdays Regular
08:00 AM & 10:00 AM Batches(Class 1Hr - 2Hrs) / Per Session
23-09-2026
Mon - FriWeekdays Regular
06:00 PM & 08:00 PM Batches(Class 1Hr - 2Hrs) / Per Session
25-09-2026
Sat-SunWeekend Batch
09:00 AM & 01:00 PM Batches(Class 2Hr - 4Hrs) / Per Session
Can't find a batch? Pick your own schedule

Vector Database Course Syllabus

This practical Vector Database Training program covers the fundamentals and advanced concepts of vector embeddings, similarity search, and Retrieval-Augmented Generation (RAG). Participants will learn to build, optimize, and deploy vector search solutions using modern vector databases and AI frameworks. The training combines hands-on labs, real-world use cases, and three practical projects to develop job-ready skills.

  • What are Vector Databases?
  • Traditional databases vs. vector databases
  • Vectors, embeddings, dimensions, and similarity
  • Use cases of vector databases
  • Vector database architecture
  • Understanding embeddings
  • Text, image, and multimodal embeddings
  • Popular embedding models
  • Chunking and preprocessing
  • Choosing embedding dimensions and models
  • Cosine similarity
  • Euclidean distance
  • Dot-product similarity
  • Nearest-neighbor search
  • Top-K retrieval
  • Filtering and metadata search
  • Introduction to major vector databases
  • Pinecone
  • Milvus
  • Chroma
  • FAISS
  • Weaviate
  • Comparing vector database architectures
  • Creating collections/indexes
  • Inserting and updating vectors
  • Metadata management
  • Batch ingestion
  • Indexing strategies
  • Data lifecycle management
  • Approximate Nearest Neighbor (ANN)
  • HNSW indexing
  • IVF and related indexing techniques
  • Hybrid search
  • Semantic + keyword search
  • Search optimization
  • Introduction to Retrieval-Augmented Generation
  • Document loading and processing
  • Chunking strategies
  • Embedding pipelines
  • Retriever design
  • Connecting vector databases with LLMs
  • LangChain integration
  • LlamaIndex integration
  • Working with embedding APIs
  • Building retrieval pipelines
  • Prompt construction
  • Context management
  • Query performance optimization
  • Scaling vector databases
  • Cost optimization
  • Authentication and access control
  • Monitoring and logging
  • Backup and recovery
  • Production deployment considerations
  • Designing a complete vector search system
  • RAG application architecture
  • Evaluation and relevance testing
  • Handling hallucinations
  • Deployment strategies
  • Industry use cases and best practices
  • Final project implementation
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Hands On Vector Database Projects

Enroll in our Vector Database classes, where our course focuses on providing high-quality training with a strong foundation in core concepts and a practical approach. Through exposure to current industry use cases and scenarios, participants will enhance their skills and gain the ability to execute real-time projects using best practice

Semantic Document Search Engine

  • Upload and process PDF/text documents
  • Generate embeddings and store them in a vector database
  • Implement semantic similarity search
  • Add metadata filtering and Top-K retrieval
  • Build a simple search interface

RAG-Based Knowledge Assistant

  • Build a document ingestion pipeline
  • Create embeddings and vector indexes
  • Connect the vector database with an LLM
  • Implement question answering using RAG
  • Add source/context retrieval and response evaluation

Enterprise AI Knowledge Platform

  • Design an end-to-end vector database architecture
  • Implement hybrid semantic and keyword search
  • Add user/metadata-based filtering
  • Optimize indexing and query performance
  • Deploy a production-ready AI knowledge assistant

For Corporates

Educate your workforce with new skills to improve their performance and productivity.

Corporate Training
"Leading Companies We've Served"
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Our Instructor
Name
Ms. Anitha
Experience
7+ Years
Specialized in
Specialized in Vector Databases, Generative AI, RAG, Embeddings, Semantic Search, LangChain, LlamaIndex, and AI application development.
More Details
The instructor is an experienced AI/ML professional specializing in practical implementation of vector search and Generative AI solutions. The training focuses on hands-on development, industry architectures, optimization techniques, and real-world AI use cases. Participants receive practical guidance through labs, projects, troubleshooting exercises, and end-to-end application development.

Vector Database Training Objectives

Our Best Vector Database Training aims to empower participants with comprehensive skills and practical knowledge in this field. Objectives include mastering core concepts, applying skills through real-world projects, critical thinking, and tackling professional challenges. This enhances career development and contributes to industry advancement.

Vector databases provide relevant information to an AI model before it generates an answer. They allow large collections of documents and knowledge to be searched based on semantic meaning. This makes them an important component of many Retrieval-Augmented Generation (RAG) systems.

You will learn embeddings, vector storage, similarity search, indexing, metadata filtering, and hybrid search. You will also learn how to integrate vector databases with LLMs, LangChain, and RAG pipelines. The course includes practical projects to help you build complete AI-powered applications.

The training introduces platforms such as Pinecone, Milvus, Chroma, FAISS, and Weaviate. The exact implementation can vary depending on the project and training environment. Participants learn the common concepts and architectures that apply across different vector database technologies.

Basic Python programming knowledge is recommended because most practical exercises involve Python-based AI tools. Understanding APIs, JSON, databases, and basic machine-learning concepts can also be helpful. The instructor can introduce the required concepts during the practical sessions.

RAG combines information retrieval with large language models to provide relevant external context to an AI system. Documents are converted into embeddings and stored in a vector database for similarity-based retrieval. The retrieved information is then supplied to the LLM to help generate a context-aware response.

You will build a semantic document search engine, a RAG-based knowledge assistant, and an enterprise AI knowledge platform. These projects cover embedding generation, vector search, retrieval pipelines, LLM integration, and optimization.

Job Assistance Program

Our Job Assistance Programme offers you special guidance through the course curriculum and helps in your interview preparation.

Specialised Curriculum
Get on-field knowledge and skills from our expert instructors.
Assessment
Upgrade your on-field skills with our assessments and track your progress in real time.
Hands-on Project
Our hands-on project help you gain experience in real-time working.
Certification Guidance
A global certificate always helps you stand out from the crowd.
Portfolio Building
Experts guide you to maximise your profile with current industry trends that employers expect.
Placment Cell
We promote your abilities and showcase your portfolio to employers.

Vector Database Career Opportunity

Vector Database is the most common programming language, and it works on all computers and mobile devices without needing to be upgraded. It is one of the highest-paying careers in the software development industry, and those with the Vector Database certification can earn an average of  8 LPA per year.

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Infibee’s placement guidance navigates you to your desired role in top organisations, ensuring you stand out and excel in every opportunity.

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.NET with MVC Training FAQ's

Infibee Vector Database Training offers wide range of services that suits for both fresher and experienced persons via both offline and online at your suitable time slots.

You need not worry about having missed a class. Our dedicated course coordinator will help them with anything and everything related to administration. The coordinator will arrange a session for the student with trainers in place of the missed one.

Yes, of course. You can contact our team at Infibee Technologies, and we will schedule a free demo or a conference call with our mentor for you.

We provide classroom, online, and self-based study material and recorded sessions for students based on their individual preferences.

Yes, all our trainers are industry professionals with extensive experience in their respective domains. They bring hands-on practical and real-world knowledge to the training sessions.

Yes, participants typically receive access to course materials, including recorded sessions, assignments, and additional resources, even after the training concludes.

We provide placement assistance to students, including resume building, interview preparation, and job placement support for a wide range of software courses.

Yes, we offer customisation of the syllabus for both individual candidates and corporate also.

Yes, we offer corporate training solutions. Companies can contact us for customised programmes tailored to their team’s needs.

Participants need a stable internet connection and a device (computer, laptop, or tablet) with the necessary software installed. Detailed technical requirements are provided upon enrollment.

In most cases, such requests can be accommodated. Participants can reach out to our support team to discuss their preferences and explore available options.

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