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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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 |
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.
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.
Practical projects can help learners understand real-world AI agent development by applying retrieval, vector search, LLM integration, and RAG concepts to application scenarios.
Infibee Technologies provides technology training programs; specific certification details and the company’s current certification partnerships should be confirmed directly before enrollment.
Infibee Technologies can offer course packages designed to provide accessible learning options, with current fees, discounts, and payment plans confirmed with the institute.
Instructor-led sessions, practical knowledge, real time exercises, doubt clarification, mock projects, and interview preparation support structured and application-oriented learning.
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.
| 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 |
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.
Basic Python and software-development knowledge can be helpful for practical exercises, although prerequisites may vary according to the particular training batch.
| 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 |
Organizations with recent job postings involving combinations of RAG, vector databases, semantic search, LLMs, or agentic AI include:
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.
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.
Upgrade Your Skills & Empower Yourself
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.
Educate your workforce with new skills to improve their performance and productivity.
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.
Our Job Assistance Programme offers you special guidance through the course curriculum and helps in your interview preparation.
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.
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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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.
We offer courses that help you improve your skills and find a job at your dream organisations.
Courses that are designed to give you top-quality skills and knowledge.
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