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AI Search & RAG Course

Rated 5 out of 5

Infibee Technologies offers India’s No.1 Industry focused AI Search & RAG Training with global certification support and job placement guidance.

Kickstart your career with our AI Search & RAG Course, is guided by 14+ years of Industry experienced experts develop practical skills in AI-powered search, Retrieval-Augmented Generation, semantic retrieval, vector databases, embeddings, and LLM-based applications. Our Course featuring practical learning, mock projects, resume preparation, interview preparation, placement training, and lifetime access to recorded sessions of live classes.

Join our AI Search & RAG Training Institute and start your AI Career to explore career opportunities in modern AI and Generative AI development.

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AI Search & RAG Course Overview

Infibee’s AI Search and Retrieval-Augmented Generation (RAG) combine intelligent search, semantic retrieval, embedding models, vector stores, and Large Language Models (LLMs) to facilitate retrieval and allow the application to produce responses based on the retrieved information. As opposed to conventional keyword-based search, AI Search allows understanding the semantics of the query and identifying semantically relevant data. RAG goes even further, retrieving relevant documents or knowledge from external sources and providing that context to the LLM prior to generating a response.

An AI Search & RAG Course at Infibee Technologies would provide learners with the opportunity to better understand how the modern retrieval-based AI systems work. This course can include such topics as embedding models, document processing, chunking, vector databases, similarity search, metadata filtering, retrieval techniques, reranking, prompt engineering, and working with LLMs. In addition, learners can get familiar with frameworks used for developing RAG applications.

There is a need for an AI Search & RAG Course due to the increasing usage of AI-based knowledge systems, enterprise search, intelligent chatbots, document assistants, and Generative AI applications. Understanding of retrieval and grounding techniques can allow building applications using the organization or domain-specific data more efficiently.

Learners will have the opportunity to gain exposure to the creation of semantic search and RAG pipelines, including connecting data sources to vector stores, assessing the effectiveness of retrieval, and using retrieved contexts with LLMs. Such competencies will be useful for AI engineers, software engineers, data engineers, and learners interested in Generative AI applications development.

Course Topics Covered Applications Tools & Technologies
Introduction to AI Search Intelligent Search Python, LLMs
Search vs. Semantic Search Enterprise Search Semantic Search
Retrieval-Augmented Generation AI Knowledge Assistants RAG, LLMs
Document Processing Document Question Answering Python, Document Loaders
Text Chunking Knowledge Retrieval LangChain, LlamaIndex
Embeddings Semantic Retrieval OpenAI, Hugging Face
Vector Databases Vector Search Pinecone, FAISS, Weaviate, Chroma
Similarity Search Context Retrieval Cosine Similarity, ANN
Metadata Filtering Filtered Search Vector Database APIs
Hybrid Search Enterprise Information Retrieval Keyword + Vector Search
Reranking Search Result Optimization Rerank Models
Prompt Engineering Context-Aware Responses LLM APIs
RAG Pipeline Development AI Chatbots LangChain, LlamaIndex
RAG Evaluation Retrieval and Response Quality Evaluation Frameworks
Production RAG Concepts AI-Powered Applications Cloud, APIs, Vector Stores

Why Choose Infibee Technologies for an AI Search & RAG Course?

  • AI Search-focused curriculum
  • RAG fundamentals
  • Semantic search concepts
  • Practical Python programming
  • Embedding generation
  • Document processing
  • Text chunking techniques
  • Vector database integration
  • Similarity search
  • Hybrid search
  • Metadata filtering
  • Retrieval strategies
  • Reranking concepts
  • LLM integration
  • LangChain exposure
  • LlamaIndex exposure
  • RAG pipeline development
  • Hands-on exercises
  • Project-based learning
  • Real-world AI application concepts
  • Enterprise search use cases
  • AI chatbot development
  • RAG evaluation concepts
  • Learning resources for continued practice
  • Training options for students and working professionals

AI Search & RAG Training Institute – Get Certified with Infibee Technologies

Infibee Technologies is one of the best, which focuses on practice-oriented learning. AI Search & RAG Training would be beneficial for students, developers, AI enthusiasts, or working professionals who wish to learn about the technology stack that is used for creating modern AI-powered search and Retrieval-Augmented Generation systems.

Hands-on and practice-oriented approach to training can focus on coding projects that will allow to learn about practical use of such technologies as semantic search, embeddings, document processing, vector databases, retrieval pipeline, reranking, prompt engineering, and integration of LLM.

Project-oriented learning can allow to use learned concepts in practice through working on projects that will give experience in creating search systems, RAG chatbots, knowledge assistants, and other systems that leverage information retrieval and Generative AI. Industry-oriented curriculum will help learners to understand the role of such technologies in modern AI development.

Infibee Technologies can also assist in preparation for interviews and career advice, helping learners to structure their technical knowledge, portfolio, CVs, and prepare for interviews.

Trainer Experience

Training emphasizes instructor-led technical learning and practical demonstrations; any specific claim of 12+ years of trainer industry experience should be confirmed directly with Infibee Technologies.

Real-Time Project Exposure

Practical projects can help learners understand real-world AI agent development by applying retrieval, vector search, LLM integration, and RAG concepts to application scenarios.

Certification / Company Background

Infibee Technologies provides technology training programs; specific certification details and the company’s current certification partnerships should be confirmed directly before enrollment.

Affordable Course Fees

Infibee Technologies can offer course packages designed to provide accessible learning options, with current fees, discounts, and payment plans confirmed with the institute.

Teaching Methodology

Instructor-led sessions, practical knowledge, real time exercises, doubt clarification, mock projects, and interview preparation support structured and application-oriented learning.

Certification

Learners may receive course-related certification or completion documentation from Infibee Technologies, depending on the selected program. Certification details, eligibility, issuing authority, and assessment requirements should be confirmed before enrollment.

Modes of AI Search & RAG Training

  • Classroom Training
  • Online Training
  • Corporate Training
  • Self-Placed Training

Global Certifications Available for AI Search & RAG Training

Serial Number Certification Code Cost Certification Expiry
1 AI-103 – Microsoft Certified: Azure AI Apps and Agents Developer Associate Region-dependent; Microsoft lists exam pricing by country 1 year
2 AWS Certified Generative AI Developer – Professional USD 300 + applicable tax; approximately ₹25,000 before applicable taxes/exchange-rate variation 3 years
3 Google Cloud Generative AI Leader USD 99 + applicable tax; approximately ₹8,300 before applicable taxes/exchange-rate variation 3 years
4 Google Cloud Professional Machine Learning Engineer USD 200 + applicable tax; approximately ₹17,000 before applicable taxes/exchange-rate variation 2 years

Who Can Join?

The AI Search & RAG Course can be suitable for learners and professionals who want to understand AI-powered search, retrieval systems, vector databases, and LLM-based applications.

  • Students pursuing AI, Machine Learning, Data Science, Computer Science, or related fields
  • Python Developers interested in Generative AI application development
  • Software Developers building AI-enabled applications
  • AI/ML Engineers working with LLMs and retrieval pipelines
  • Data Scientists exploring semantic search and knowledge retrieval
  • Data Engineers working with enterprise data and AI pipelines
  • Backend Developers integrating LLMs, APIs, and vector databases
  • Generative AI Developers building RAG-based applications
  • LLM Application Developers working with retrieval and contextual generation
  • Search Engineers interested in semantic and hybrid search
  • Cloud Professionals developing cloud-based AI solutions
  • MLOps Professionals supporting production AI workloads
  • Working Professionals looking to expand their Generative AI skills
  • AI Enthusiasts seeking practical exposure to RAG and AI Search

Basic Python and software-development knowledge can be helpful for practical exercises, although prerequisites may vary according to the particular training batch.

Career Opportunities in AI Search & RAG

Job Role Relevant Skills Application Area
Generative AI Engineer RAG, LLMs, embeddings, vector databases GenAI applications
RAG Engineer Retrieval pipelines, chunking, embeddings, reranking Knowledge systems
AI Search Engineer Semantic search, vector search, hybrid search Intelligent search
AI Engineer LLM integration, APIs, RAG, Python AI applications
Agentic AI Engineer Agents, RAG, tools, vector stores AI agent systems
LLM Engineer LLM integration, retrieval, evaluation LLM applications
AI Application Developer Python, APIs, RAG, LLMs AI-powered software
Machine Learning Engineer ML pipelines, embeddings, model integration Production AI
AI Platform Engineer Vector infrastructure, APIs, cloud AI Enterprise AI platforms
Data Engineer – GenAI Data pipelines, embeddings, indexing, vector databases AI data systems
Search/Information Retrieval Engineer Ranking, retrieval, semantic search Search platforms
AI Solutions Architect RAG architecture, LLMs, cloud AI Enterprise AI architecture
MLOps/LLMOps Engineer Deployment, monitoring, evaluation, AI infrastructure Production GenAI

Who’s Hiring Advanced AI Search & RAG Professionals?

Organizations with recent job postings involving combinations of RAG, vector databases, semantic search, LLMs, or agentic AI include:

  1. Mindera — Data Engineer – Generative AI & Vector Systems, Chennai.
  2. HCLTech — GenAI Engineer / VectorDB-related roles involving LLMs, vector databases, and Azure AI Search.
  3. Birlasoft — Generative AI leadership roles involving RAG and vector databases.
  4. AgileEngine — Lead AI/Agentic AI roles involving RAG, vector databases, LLM APIs, and agentic workflows.
  5. Ubique Systems — Generative AI Backend Engineer roles involving RAG pipelines, vector databases, semantic search, and AI agents.
  6. Inlogic Technologies — AI Engineer roles involving LangChain, RAG, vector databases, multi-agent systems, and Azure AI Search.
  7. Walbrydge Technologies — AI/Generative AI roles listing RAG, vector databases, LLMs, APIs, and cloud AI services.

Can I Study AI Search & RAG in Other Locations?

How to Register for the AI Search & RAG Course at Infibee Technologies?

Step 1: Contact Infibee Technologies

Seek out information on the AI Search & RAG Course, its syllabus, costs, prerequisites, next batches, and current modes of training offered.

Step 2: Join a Demo or Course Discussion

In case a demo is available, join it to know how the course is structured and taught, what kind of practice is included, and the overall learning approach.

Step 3: Complete the Enrollment Process

Choose the right mode of training and enroll yourself through the guidelines provided by Infibee Technologies.

Enroll Today: Unlock Your AI Search & RAG Training Potential

Contact Infibee Technologies to explore the AI Search & RAG Course, check upcoming batches, attend a demo if available, and choose a learning format suited to your goals.

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Why People Choose Infibee ?

Upcoming AI Search & RAG Batches

[dateshortCodeCi day=' monday ' ]
Mon-FriWeekdays Regular
08:00 AM & 10:00 AM Batches(Class 1Hr - 2Hrs) / Per Session
[dateshortCodeCi day=' wednesday ' ]
Mon - FriWeekdays Regular
06:00 PM & 08:00 PM Batches(Class 1Hr - 2Hrs) / Per Session
[dateshortCodeCi day=' Friday ' ]
Sat-SunWeekend Batch
09:00 AM & 01:00 PM Batches(Class 2Hr - 4Hrs) / Per Session
Can't find a batch? Pick your own schedule

AI Search & RAG Course Syllabus

This practical AI Search & RAG Training program covers modern search systems, embeddings, retrieval techniques, and Retrieval-Augmented Generation (RAG). Participants will learn to build intelligent search and question-answering applications using LLMs, vector databases, hybrid search, and reranking. The training combines concepts, hands-on labs, real-world use cases, and end-to-end projects for practical AI development.

  • Evolution of search: keyword to semantic search
  • What is AI Search?
  • What is Retrieval-Augmented Generation?
  • RAG architecture and workflow
  • RAG vs. fine-tuning
  • Real-world applications
  • Document loading and parsing
  • PDF, Word, HTML, and text processing
  • Text cleaning and normalization
  • Document metadata
  • Tokenization concepts
  • Preparing data for retrieval
  • Understanding embeddings
  • Text embedding models
  • Semantic similarity
  • Cosine similarity and vector distance
  • Query embeddings
  • Building semantic search pipelines
  • Vector database fundamentals
  • Pinecone, Milvus, Chroma, FAISS, and Weaviate
  • Collections, indexes, and metadata
  • Approximate Nearest Neighbor search
  • HNSW and indexing concepts
  • Vector database integration
  • Complete RAG architecture
  • Document ingestion pipeline
  • Chunking strategies
  • Embedding generation
  • Retrieval pipeline
  • Context construction
  • Connecting retrieved context to LLMs
  • Keyword search vs. semantic search
  • Hybrid search
  • Metadata filtering
  • Query expansion
  • Multi-query retrieval
  • Parent-child and contextual retrieval
  • Reranking techniques
  • LLM integration for RAG
  • LangChain
  • LlamaIndex
  • Prompt templates
  • Retrieval chains
  • Conversational RAG
  • Managing conversation context
  • Multi-step retrieval
  • Query routing
  • Self-query retrieval
  • Agentic RAG concepts
  • Tool-based search
  • Knowledge graphs with RAG
  • Multimodal RAG fundamentals
  • Retrieval evaluation
  • Answer quality evaluation
  • Precision, recall, and relevance
  • RAG evaluation frameworks
  • Hallucination reduction
  • Prompt injection and data security
  • Latency and cost optimization
  • Production RAG architecture
  • API development
  • Monitoring and logging
  • Scaling AI search systems
  • Caching and performance optimization
  • Deployment strategies
  • Industry use cases and best practices
Need customized curriculum?
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Hands On AI Search & RAG Projects

Enroll in our AI Search & RAG 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

AI-Powered Enterprise Document Search

  • Upload and process enterprise documents
  • Generate embeddings and create a searchable knowledge base
  • Implement semantic and keyword search
  • Add metadata-based filtering
  • Build an AI-powered search interface

RAG-Based Intelligent Knowledge Assistant

  • Build a complete document ingestion pipeline
  • Implement chunking and embedding generation
  • Connect a vector database with an LLM
  • Build contextual question answering
  • Add conversational memory and source references

Advanced Agentic RAG Search Platform

  • Design an advanced RAG architecture
  • Implement hybrid search and reranking
  • Add query routing and multi-step retrieval
  • Integrate tools and external knowledge sources
  • Evaluate, optimize, and deploy the application

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
Mr. Murali
Experience
11+ Years
Specialized in
Specialized in Generative AI, AI Search, RAG, LLMs, Vector Databases, Embeddings, LangChain, LlamaIndex, and Agentic AI.
More Details
The instructor is an experienced AI professional specializing in Generative AI, intelligent search, RAG architectures, and LLM-based applications. The training emphasizes practical implementation using modern AI frameworks, retrieval technologies, vector databases, and production architectures. Participants receive hands-on guidance through labs, real-world scenarios, troubleshooting exercises, and end-to-end AI projects.

AI Search & RAG Training Objectives

Our Best AI Search & RAG 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.

RAG combines information retrieval with a Large Language Model to generate answers using relevant external information. Documents are processed and indexed so that relevant content can be retrieved when a user asks a question. The retrieved context is then provided to the LLM to generate a more grounded response.

RAG retrieves information from an external knowledge source at query time and provides it to the LLM as context. Fine-tuning modifies a model’s learned behavior using additional training data. RAG is particularly useful when the knowledge base changes frequently or needs source-based retrieval.

You will learn embeddings, semantic search, vector databases, hybrid retrieval, reranking, and RAG architectures. The course also covers LangChain, LlamaIndex, LLM integration, RAG evaluation, security, and optimization. Hands-on projects provide experience building complete AI search and RAG applications.

The training can cover vector databases such as Pinecone, Milvus, Chroma, FAISS, and Weaviate. Modern AI frameworks such as LangChain and LlamaIndex are used for building retrieval and RAG pipelines. The exact tools can be adapted to the project requirements and current enterprise technology stack.

RAG gives an LLM relevant information retrieved from a defined knowledge source before generating an answer. This can improve factual grounding when retrieval is accurate and the model follows the supplied context. However, RAG does not eliminate hallucinations, so retrieval and generation quality must be evaluated separately.

You will build an AI-powered enterprise document search system, a RAG-based knowledge assistant, and an advanced agentic RAG platform. The projects cover document processing, embeddings, vector search, hybrid retrieval, reranking, and LLM integration. You will also work with evaluation, optimization, security, and production deployment concepts.

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.

AI Search & RAG Career Opportunity

AI Search & RAG 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 AI Search & RAG certification can earn an average of  8 LPA per year.

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Placement Guidance & Interview Preparation

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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AI Search & RAG Training FAQ's

Infibee AI Search & RAG 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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