Practical, AI-supported, and directly applicable – this course links business intelligence with modern analytics tools and builds expertise for data-driven decisions in complex environments.

AI-powered data agents automate information workflows, structure datasets, and build foundations for smart, efficient processes in modern digital environments.

Data and AI combine into a powerful toolkit for analysis, decisions, and automation – practical and immediately applicable in professional settings.

AI meets research practice – a compact course for professionals seeking to analyze data confidently, apply AI tools effectively, and communicate findings clearly.

From raw data to clear insights – structured training for those who analyze data, recognize patterns, and want to support data-driven decisions professionally.

Database operations, security, and governance in a practical format – for IT professionals who want to manage data infrastructures with confidence.

Core techniques of Transact-SQL covered in a compact format – for IT professionals, analysts, and anyone querying and evaluating data in SQL Server.

Administering Azure SQL confidently: from initial setup and monitoring to performance tuning and high availability – hands-on for real cloud operations.

Applying Azure Cosmos DB purposefully: data modeling, global replication, and performance tuning for cloud-native applications with high availability requirements.

Microsoft Fabric as an end-to-end analytics platform: pipelines, lakehouses, data warehousing, and Power BI in practical use for data-intensive scenarios.

Implement lakehouse architectures with Microsoft Fabric: integrate data from various sources, process with Spark and Delta Lake, and prepare for analytics.

Building scalable data warehouses in Microsoft Fabric: integrating, transforming, and preparing data for analytics – with a focus on architecture, performance, and operations.

Real-time analytics in Microsoft Fabric: event streams, KQL databases, and scalable architectures – for immediate data evaluation and data-driven decisions.

Deepen your Power BI skills: learn how to develop dynamic reports, prepare data interactively, and apply DAX concepts efficiently in practice.

Integrated data workflows with Microsoft Fabric: from data integration and real-time streams to warehouse security – structured for hands-on application.

Practical course for data engineers building production cloud pipelines with Azure Databricks – covering Apache Spark, Delta Lake, Lakeflow, and automated workflows end to end.

AI integration makes databases more efficient and analytically powerful. This training covers SQL-based approaches for Azure, security, performance, and intelligent search solutions.

This course covers the essentials of data structures, cloud workloads, and analytics tools in Azure. Suitable for anyone interested in modern data platforms.

Structured migration of SQL Server to Azure SQL – covering architecture, security, performance, and long-term stability of cloud data platforms.

Practical knowledge for NoSQL development with Azure Cosmos DB: data modeling, queries, indexing, SDK integration, and partitioning strategies for scalable cloud applications.

Practical knowledge for developing data-driven applications with Azure SQL Database: deployment options, CI/CD integration, data APIs, and security configuration in the cloud.

Practical knowledge for configuring and migrating Azure Database for PostgreSQL: architecture, security, performance optimization, and migration techniques.

Practical application of Copilot in Microsoft Fabric: automating data workflows, AI-powered analysis, and efficient report creation for data-driven organizations.

Data preparation, modeling, and visualization with Microsoft Power BI – for analysts who transform raw data into clear insights and well-founded reports in any organization.

Build custom apps with Microsoft PowerApps – integrate data, digitize business processes, and implement efficient workflows across teams.

Automate recurring tasks and manage workflows efficiently with Microsoft Power Automate – for greater productivity in everyday working life.

Fundamentals of Python syntax and logic, working with data structures, and first steps in automation and data science – clearly structured for beginners.

Statistical data analysis, visualization, and machine learning fundamentals with Python – hands-on and practical for professionals in technology, IT, and science.

Machine learning fundamentals, data preparation, and model deployment with Python – practical for professionals in IT, data science, analytics, and related fields.

A structured introduction to Tableau – from connecting data to dashboard design and the clear visualization of key metrics and trends for professionals in analysis and reporting.

From the first step in Tableau to a finished dashboard – Tableau Desktop Part 1 shows how to connect data sources, structure analyses, and present results clearly.

Tableau Desktop Part 2 deepens advanced analytics techniques: data blending, complex calculations, LOD expressions, and interactive dashboard design for data professionals.