Data Analyst und AI Specialist

Der Azure Data Analyst ist für die Analyse und Interpretation großer Datenmengen in der Azure-Cloud-Umgebung verantwortlich.
Die Hauptaufgabe besteht darin, Datenpipelines zu entwerfen, zu entwickeln und zu warten, um relevante Informationen aus verschiedenen Datenquellen zu extrahieren.

Microsoft Azure AI Engineers erstellen, verwalten und stellen KI-Lösungen bereit, die Azure Cognitive Services und Azure-Dienste nutzen. Zu ihren Aufgaben gehört es, an allen Phasen der Entwicklung von KI-Lösungen mitzuwirken – von der Anforderungsdefinition und dem Entwurf über die Entwicklung, die Bereitstellung, die Integration und die Wartung bis hin zur Leistungsoptimierung und Überwachung.

AZ-900 Praxis+ Microsoft Azure Fundamentals

• Describe Core Azure ConceptsI
• Describe Core Azure Services
• Describe Core Solutions and Management Tools on Azure
• Describe general Security and Network Security Features
• Describe Identity, Governance, Privacy and Compliance Features
• Describe Azure Cost Management and Service Level Agreements

AI-900 Microsoft Azure AI Fundamentals

• Fundamental AI Concepts
• Fundamentals of machine learning
• Fundamentals of Azure AI services
• Fundamentals of Computer Vision
• Fundamentals of Facial Recognition
• Fundamentals of optical character recognition
• Fundamentals of Text Analysis with the Language Service
• Fundamentals of question answering with the Language Service
• Fundamentals of conversational language understanding
• Fundamentals of Azure AI Speech
• Fundamentals of Azure AI Document Intelligence
• Fundamentals of Knowledge Mining with Azure Cognitive Search
• Fundamentals of Generative AI
• Fundamentals of Responsible Generative AI

DP-900 Microsoft Azure Data Fundamentals

• Explore core data concepts
• Explore data roles and services
• Explore fundamental relational data concepts
• Explore relational database services in Azure
• Explore Azure Storage for non-relational data
• Explore fundamentals of Azure Cosmos DB
• Explore fundamentals of large-scale analytics
• Explore fundamentals of real-time analytics
• Explore fundamentals of data visualization

DP-203 Data Engineering on Microsoft Azure

• Introduction to data engineering on Azure
• Introduction to Azure Data Lake Storage Gen2
• Introduction to Azure Synapse Analytics
• Use Azure Synapse serverless SQL pool to query files in a data lake
• Use Azure Synapse serverless SQL pools to transform data in a data lake
• Create a lake database in Azure Synapse Analytics
• Analyze data with Apache Spark in Azure Synapse Analytics
• Transform data with Spark in Azure Synapse Analytics
• Use Delta Lake in Azure Synapse Analytics
• Analyze data in a relational data warehouse
• Load data into a relational data warehouse
• Build a data pipeline in Azure Synapse Analytics
• Use Spark Notebooks in an Azure Synapse Pipeline
• Plan hybrid transactional and analytical processing using Azure Synapse Analytics
• Implement Azure Synapse Link with Azure Cosmos DB
• Implement Azure Synapse Link for SQL
• Get started with Azure Stream Analytics
• Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
• Visualize real-time data with Azure Stream Analytics and Power BI
• Introduction to Microsoft Purview
• Integrate Microsoft Purview and Azure Synapse Analytics
• Explore Azure Databricks
• Use Apache Spark in Azure Databricks
• Run Azure Databricks Notebooks with Azure Data Factory

PL-300 Microsoft Power BI Data Analyst

• Discover data analysis
• Get started building with Power BI
• Get data in Power BI
• Clean, transform, and load data in Power BI
• Design a data model in Power BI
• Add measures to Power BI Desktop models
• Add calculated tables and columns to Power BI Desktop models
• Use DAX time intelligence functions in Power BI Desktop models
• Optimize a model for performance in Power BI
• Design Power BI reports
• Configure Power BI report filters
• Enhance Power BI report designs for the user experience
• Perform analytics in Power BI
• Create and manage workspaces in Power BI
• Manage datasets in Power BI
• Create dashboards in Power BI
• Implement row-level security

AI-102 Designing and Implementing a Microsoft Azure AI Solution

• Prepare to develop AI solutions on Azure
• Create and consume Azure AI Services
• Secure Azure AI Services
• Monitor Azure AI Services
• Deploy Azure AI services in containers
• Extract insights from text with the Azure AI Language service
• Translate text with the Azure AI Translator service
• Create speech-enabled apps with the Azure AI Speech service
• Translate speech with the Azure AI Speech service
• Build an Azure AI Language Understanding model
• Publish and use an Azure AI Language Understanding app
• Build a question answering solution
• Create a bot with the Bot Framework SDK
• Create a Bot with the Bot Framework Composer
• Analyze images
• Analyze video
• Classify images
• Detect objects in images
• Detect, analyze, and recognize faces
• Read Text in Images and Documents with the Azure AI Vision Service
• Extract data from forms with Azure Document Intelligence
• Create an Azure Cognitive Search solution
• Create a custom skill for Azure Cognitive Search
• Create a knowledge store with Azure Cognitive Search

Data SkillBoost

• Planung des abzubildenden Businessprozesses und Erstellung der Mandanten
• Einrichtung des Identitätsproviders, Erstellung der DW Portale und Transport Ressourcen
• Erstellen der ETL Prozesse. Aufbau des Data Warehouse
• Anpassen der Data Ware House Lösung durch Integration der Delta Lake Architektur.
• Erstellen einer KI-Lösung zum Erkennen von Anomalien.
• Erstellen eine (nahe) Echtzeit Datenstroms und er dazugehörigen Komponenten.
• Erstellen der Reportings

Scrum Foundation für Scrum Master und Product Owner

• Prinzipien und zugrundeliegende Theorie von Scrum
• Überblick über das Scrum Team
• Scrum Events
• Scrum Artefakte
• Die Rolle des Scrum Master
• Die Rolle des Product Owner
• Theorie-Input & Erfahrungslernen
• Vorbereitung auf die Zertifizierungen