The path to becoming a data scientist combines cloud technologies, data analysis, AI, and programming into a compact package. The focus is clearly on core skills in Microsoft Azure, SQL, and Python, as well as practical data handling.

The program is aimed at career changers and IT-savvy professionals who want to get started in the field of data, AI, and machine learning. Modern content, practical application, and flexible implementation create a strong foundation for data-based projects and new career prospects.

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modules
  • Introduction to artificial intelligence concepts and their practical use in Azure. The focus is on machine learning, computer vision, and speech processing.

    Certification: Microsoft Azure AI Fundamentals

  • Provides a fundamental understanding of cloud models, Azure services, security, and compliance aspects. The module lays the foundation for the secure use of the Azure platform and cloud-based solutions.

    Certification: Microsoft Azure Fundamentals

  • Covers core database and data processing concepts. Content includes relational and non-relational data, query fundamentals, and analytical workloads in Azure.

    Certification: Microsoft Azure Data Fundamentals

  • Overview of the components of the Power Platform. Teaches the basics of Power BI, Power Apps, and Power Automate for analyzing, automating, and optimizing business processes.

    Certification: Microsoft Power Platform Fundamentals

  • Advanced professional Power BI skills. Topics include data preparation, modeling, DAX, performance optimization, and the development of complex reports and dashboards.

    Certification: Microsoft Power BI Data Analyst Associate

  • Deepens the use of Excel for data analysis. Topics include data preparation, formulas, functions, pivot tables, and basic visualizations as a basis for meaningful evaluations.

    Certification: New Horizons Certificate of Participation

  • Focus on the practical use of Power BI for analyzing and visualizing data. Learn how to create interactive reports, dashboards, and simple data models.

    Certification: New Horizons Certificate of Participation

  • Python: Covers basics and advanced topics, machine learning with Python, and the development path from data analyst to data scientist.
  • CompTIA Data+: Provides practical knowledge of data analysis and prepares you specifically for the recognized certification exam.
  • EXIN® Agile Scrum Foundation: Introduction to agile working methods with a focus on the roles, processes, and principles of Scrum.
  • ITIL® 4 Foundation with exam: Basic introduction to IT service management according to ITIL®best practices and standards.
  • PRINCE2® 7 Foundation with exam: Covers methods, processes, and roles of structured project management according to PRINCE2®.

Start date: You can start anytime.
Duration: 6.25 months full-time; if you're doing it part-time, it'll take a bit longer. How
it works: Live online classes mixed with guided learning phases and focused exam prep.
Location: Flexible and location-independent, at the training center or from home.

Target group:
Aimed at people who are interested in data analysis, reporting, and business intelligence and want to build or expand their skills in Microsoft technologies, Excel, and Power BI. Suitable for career starters, career changers, and professionals who want to take on or deepen their knowledge of data-based tasks.

Prerequisites:
Basic PC skills and a basic understanding of technology are required. Initial experience with data, tables, or evaluations is advantageous but not required. Basic English skills are recommended, as some content and exams are in English.

Funding: Full coverage
of costs is possible through the education voucher from the Employment Agency. In addition, funding programs are available for employees and companies under the Qualification Opportunities Act.

We are AZAV certified
: The program is AZAV-certified and geared towards current requirements in the field of data analytics. The modular structure supports a flexible learning structure and sustainable qualification for data-oriented professions.