Build an AI App with Azure using RAG Training

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  • Project Based Learning
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Build an AI App with Azure using RAG Training Course Overview

Unlock the power of AI with Build an AI App with Azure using RAG Training by Multisoft Systems. Learn how to develop intelligent applications using Retrieval-Augmented Generation (RAG) on Azure. Gain hands-on expertise in AI-driven data retrieval, model integration, and response optimization for smarter and more efficient AI applications.

The Build an AI App with Azure using RAG Training by Multisoft Systems is designed to equip professionals with the skills required to develop intelligent AI-powered applications leveraging Retrieval-Augmented Generation (RAG) on Azure. This course focuses on integrating AI models with retrieval-based methodologies to enhance data access, improve response accuracy, and optimize AI-driven decision-making. Participants will gain hands-on experience with Azure AI services, learning how to build and deploy AI applications that intelligently retrieve and process data to generate contextually relevant responses. The training covers natural language processing (NLP), vector databases, model fine-tuning, and AI-based content generation. By leveraging Azure OpenAI Service, Cognitive Search, and Azure Machine Learning, learners will explore how RAG enhances AI models by combining real-time data retrieval with generative AI capabilities. This course is ideal for AI developers, data scientists, cloud engineers, and professionals looking to enhance their expertise in AI-driven application development. By the end of the training, participants will have the skills to implement RAG models, integrate them into AI applications, and optimize AI-driven solutions on Microsoft Azure for various real-world scenarios.

Join Multisoft Systems to gain in-demand AI skills and stay ahead in the rapidly evolving AI landscape!

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Build an AI App with Azure using RAG Training Course curriculum

Curriculum Designed by Experts

Unlock the power of AI with Build an AI App with Azure using RAG Training by Multisoft Systems. Learn how to develop intelligent applications using Retrieval-Augmented Generation (RAG) on Azure. Gain hands-on expertise in AI-driven data retrieval, model integration, and response optimization for smarter and more efficient AI applications.

The Build an AI App with Azure using RAG Training by Multisoft Systems is designed to equip professionals with the skills required to develop intelligent AI-powered applications leveraging Retrieval-Augmented Generation (RAG) on Azure. This course focuses on integrating AI models with retrieval-based methodologies to enhance data access, improve response accuracy, and optimize AI-driven decision-making. Participants will gain hands-on experience with Azure AI services, learning how to build and deploy AI applications that intelligently retrieve and process data to generate contextually relevant responses. The training covers natural language processing (NLP), vector databases, model fine-tuning, and AI-based content generation. By leveraging Azure OpenAI Service, Cognitive Search, and Azure Machine Learning, learners will explore how RAG enhances AI models by combining real-time data retrieval with generative AI capabilities. This course is ideal for AI developers, data scientists, cloud engineers, and professionals looking to enhance their expertise in AI-driven application development. By the end of the training, participants will have the skills to implement RAG models, integrate them into AI applications, and optimize AI-driven solutions on Microsoft Azure for various real-world scenarios.

Join Multisoft Systems to gain in-demand AI skills and stay ahead in the rapidly evolving AI landscape!

  • Understand the fundamentals of Retrieval-Augmented Generation (RAG) and its applications in AI.
  • Learn to develop AI-powered applications using Azure's AI services.
  • Gain expertise in Azure OpenAI Service, Cognitive Search, and Azure Machine Learning.
  • Implement RAG models for intelligent data retrieval and content generation.
  • Optimize AI-generated responses using retrieved contextual data.
  • Learn vector database integration for efficient information retrieval.
  • Explore natural language processing (NLP) techniques for enhancing AI models.
  • Build and deploy AI solutions using Azure cloud infrastructure.

Course Prerequisite

  • Basic understanding of Artificial Intelligence (AI) and Machine Learning (ML)
  • Familiarity with Azure AI services and cloud computing
  • Knowledge of Python programming

Course Target Audience

  • AI Developers
  • Data Scientists
  • Cloud Engineers
  • Machine Learning Engineers
  • Software Developers
  • Solution Architects
  • AI and Cloud Consultants
  • IT Professionals
  • Research Analysts
  • Business Intelligence Professionals

Course Content

  • Learn vCore-based Azure Cosmos DB for MongoDB 
  • Create a vCore-based Azure Cosmos DB for MongoDB cluster 
  • Deploy a vCore-based Azure Cosmos DB for MongoDB cluster 

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  • Migration assessment and planning 
  • Offline migration from MongoDB to vCore-based Azure Cosmos DB for MongoDB using MongoDB native tools 
  • Offline migration from MongoDB to vCore-based Azure Cosmos DB for MongoDB using Azure Data Studio 
  • Migrate Data from MongoDB to vCore-based Azure Cosmos DB for MongoDB using Azure Databricks 
  • Migrate to vCore-based Azure Cosmos DB for MongoDB with MongoDB native tools 

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  • Scale and configure a vCore-based Azure Cosmos DB for MongoDB cluster 
  • Explore high availability in a vCore-based Azure Cosmos DB for MongoDB cluster 
  • Backup and restore a vCore-based Azure Cosmos DB for MongoDB cluster 
  • Monitor a vCore-based Azure Cosmos DB for MongoDB cluster 
  • Manage a vCore-based Azure Cosmos DB form MongoDB cluster 

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  • Explore Azure OpenAI 
  • Understand vector databases, Retrieval Augmentation Generation, and embeddings in AI 
  • Implement Retrieval Augmentation Generation using vector indexes in vCore based Azure Cosmos DB for MongoDB 
  • Develop an AI copilot using vCore-based Azure Cosmos DB for MongoDB and Azure OpenAI 

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  • Deploy applications with Azure Kubernetes Service 
  • Create containerized apps with Azure Kubernetes Service clusters 
  • Prepare your copilot application 
  • Create an Azure Kubernetes Service cluster

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Build an AI App with Azure using RAG Training (MCQ) Assessment

This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :

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Build an AI App with Azure using RAG Training FAQ's

Retrieval-Augmented Generation (RAG) is an AI technique that enhances generative models by retrieving relevant data from external sources before generating responses, improving accuracy and relevance.

This course is ideal for AI developers, data scientists, cloud engineers, software developers, and IT professionals looking to build AI applications using Azure AI services.

Participants should have a basic understanding of AI, machine learning, Python programming, NLP, and Azure AI services.

The training covers Azure OpenAI Service, Cognitive Search, Azure Machine Learning, vector databases, NLP techniques, and cloud-based AI deployment.

To contact Multisoft Systems you can mail us on info@multisoftsystems.com or can call for course enquiry on this number +91 9810306956

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