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Design and Deploy a Real-Time Intelligence Solution Using Microsoft Fabric

This intermediate-level custom training equips learners to build and deploy a real-time intelligence solution using Microsoft Fabric. Participants will prepare a Real-Time Analytics environment, ingest and process streaming data with Eventstreams, manage and query data in Eventhouse, and build dynamic dashboards for live insights. The course also introduces Activator for triggering downstream actions based on real-time events.

Design and Deploy a Data Warehouse Using Microsoft Fabric

This intermediate-level custom training focuses on implementing a data warehouse in Microsoft Fabric by guiding learners through creating a warehouse, loading and transforming data—including Slowly Changing Dimension (SCD) Type 2 techniques, modeling a star schema, querying with T-SQL, and managing security, all within Fabric’s unified analytics environment.

Design and Deploy a Lakehouse Architecture Using Microsoft Fabric

This intermediate-level custom training teaches learners how to implement a lakehouse architecture using Microsoft Fabric, enabling unified data storage, transformation, and analytics. Participants will create and manage lakehouses, ingest data with Dataflows Gen2, transform and query data using Apache Spark and Delta Lake tables, and orchestrate workflows with medallion architecture design.

Design and Deploy Data Science & ML Workflows for AI in Microsoft Fabric

This intermediate-level custom training guides learners through building and operationalizing a full data science and machine learning solution using Microsoft Fabric. Participants will ingest and explore data with Lakehouses and Notebooks, prepare it using Data Wrangler, train and track models via MLflow, and deploy them for batch predictions—all within Fabric’s unified analytics environment.

Modernizing SQL Workloads: Migrating to Azure SQL Database

This intermediate-level custom training prepares learners to assess and migrate SQL Server workloads to Azure SQL Database using both IaaS and PaaS strategies. Participants will design a migration plan, evaluate database readiness, provision Azure SQL resources, and execute migrations to Azure Virtual Machines, Azure SQL Database, and Azure SQL Managed Instance. The course also covers post-migration configuration and disaster recovery setup.

Modernizing PostgreSQL Workloads: Configuring and Migrating to Azure Database for PostgreSQL

This intermediate-level custom training equips data engineers and architects to configure, secure, and migrate PostgreSQL workloads to Azure Database for PostgreSQL. Participants will learn to assess on-prem environments, choose the right deployment model, and implement scalable, cloud-native solutions with governance, performance, and cost-efficiency in mind.

Building Generative AI Applications with Azure AI Foundry

This intermediate-level custom training offers a comprehensive, hands-on journey through building generative AI applications in Azure using the AI Foundry platform. Participants will learn to plan and prepare development environments, select and deploy models from a curated catalog, build applications using the Azure AI Foundry SDK, and structure interactions with prompt flow. The course also covers Retrieval Augmented Generation (RAG) using custom data, fine-tuning open-source language models, implementing responsible AI practices to mitigate risks, and evaluating copilot performance for continuous improvement, all within a scalable, enterprise-ready framework

Building AI-Driven Applications with Azure Database for PostgreSQL

This intermediate-level custom training, covers the end-to-end integration of Azure AI services with Azure Database for PostgreSQL – Flexible Server, enabling participants to build intelligent, data-driven applications. Key concepts include deploying generative AI using Azure AI extensions, implementing semantic search with vector embeddings, applying summarization and sentiment analysis to text data, extracting structured insights through language understanding, translating multilingual content for global accessibility, and operationalizing machine learning models via AutoML for real-time inferencing, all directly within PostgreSQL workflows.

Designing Intelligent Knowledge Mining Solutions with Azure AI Search

This intermediate-level custom training, covers the full lifecycle of implementing intelligent search with Azure AI Search, including solution architecture, indexing strategies, custom skill integration, enrichment pipelines, and knowledge store creation; learners also explore advanced capabilities like semantic ranking, vector-based retrieval, multilingual search, external data ingestion via Azure Data Factory, and performance optimization to build scalable, AI-enhanced search experiences across enterprise scenarios

Developing AI Agents on Azure: From Prompt to Context Engineering to Production

This intermediate-level custom training, focuses on designing and deploying intelligent AI agents using Azure AI Foundry and the Microsoft Agent Framework. Participants will learn to build agents with the Azure AI Foundry Agent Service, integrate custom and MCP-hosted tools, and orchestrate multi-agent systems for complex task execution. Key features include agent-to-agent (A2A) communication protocols, remote agent discovery, and SDK-based orchestration for scalable, collaborative AI solutions, all within a secure, enterprise-ready Azure environment.

Developing Computer Vision Solutions with Azure AI Services

This intermediate-level custom training covers the end-to-end development of computer vision solutions using Azure AI Vision, focusing on key technical concepts such as image analysis with prebuilt models, optical character recognition (OCR) for text extraction, face detection and emotion recognition, custom image classification and object detection, and video content analysis using Azure Video Indexer. Participants will also learn to integrate these capabilities into generative AI applications and explore image generation using AI models, all while applying best practices for scalability, cost optimization, and data privacy compliance

Creating Intelligent Agents with Microsoft Copilot Studio

This intermediate-level custom training covers the end-to-end process of building intelligent, no-code agents in Microsoft Copilot Studio, focusing on key technical concepts such as topic creation and management, entity and variable handling for dynamic conversations, agent design principles for effective user interaction, integration with Power Automate and Omnichannel for enhanced functionality, deployment within Dataverse for Teams, and autonomous agent development using Generative AI and natural language inputs.

Implementing Scalable Data Analytics Solutions with Azure Databricks

This intermediate-level custom training covers the full lifecycle of building scalable analytics solutions in Azure Databricks, starting with workspace navigation and cluster setup, followed by data ingestion and exploratory analysis using Spark DataFrames, SQL, and PySpark. Participants then dive into distributed processing with Apache Spark, manage reliable datasets using Delta Lake’s ACID transactions and time travel, and orchestrate real-time and batch workflows through Lakeflow declarative pipelines and Jobs.

Designing Generative AI Pipelines in Azure Databricks: From Foundation Models to Deployment

This intermediate-level custom training focuses on implementing generative AI solutions using Azure Databricks, emphasizing the full lifecycle of Large Language Models (LLMs). Key technical concepts include natural language processing (NLP) tasks, Retrieval Augmented Generation (RAG), multi-stage reasoning, and fine-tuning LLMs for domain-specific applications. Learners also explore model evaluation techniques—including automated methods like LLM-as-a-judge, alongside responsible AI principles and security tooling.

Building Machine Learning Solutions with Azure Databricks: From Data to Deployment

This intermediate-level custom covers the full lifecycle of building machine learning solutions using Azure Databricks, starting with scalable data analytics via Apache Spark and progressing through model development, evaluation, and deployment. Participants learn to train ML and deep learning models using popular frameworks, manage experiments and model versions with MLflow, optimize performance through hyperparameter tuning and AutoML, and operationalize models for real-time decision-making.

Transform and Visualize Your Data with Power BI

This beginner-level custom training covers the full technical lifecycle of preparing and visualizing data with Power BI and Microsoft Fabric. Participants will learn to connect to structured and unstructured data sources, clean and transform data using Power Query, and build semantic models for scalable reporting. The course emphasizes designing interactive reports with advanced filtering, dynamic visuals, and performance optimization. Learners will also explore Copilot integration for natural language querying and report generation.

Design and Deploy AI-Powered Information Extraction in Azure

This intermediate-level custom training empowers Data, Analyst, ML & AI Engineers and Developers to build intelligent solutions that extract structured insights from unstructured content using Azure AI. Key concepts include multimodal content analysis with Azure AI Content Understanding, client application development via REST APIs, and leveraging prebuilt and custom document intelligence models for form data extraction. Participants also learn to implement scalable knowledge mining solutions using Azure AI Search, enabling enriched, searchable data.

Design and Deploy Natural Language Solutions with Azure AI

This intermediate-level custom training equips learners to build intelligent language solutions using Azure AI Language and Speech services. Key concepts include text analytics (sentiment, key phrases, entities), question answering, conversational language understanding, custom text classification, and named entity recognition. It also covers multilingual translation for both text and speech, speech-to-text and text-to-speech integration, and audio-enabled generative AI applications that interpret tone, intent, and spoken input to deliver dynamic, voice-driven experiences.

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