Mastering Data Analysis with Generative AI: A Comprehensive Training Guide
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This article outlines a training program focused on leveraging Generative AI (GenAI) for data analysis. It covers the fundamentals of GenAI, its applications in data preparation, cleaning, integration, and predictive analytics, with a particular emphasis on enhancing Microsoft Excel and Data Science workflows. The program includes practical exercises, discussions on ethical considerations, and an overview of relevant tools like Microsoft Copilot Studio. It aims to equip participants with the skills to automate processes, gain insights from unstructured data, and create AI-powered dashboards.
main points
unique insights
practical applications
key topics
key insights
learning outcomes
• main points
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Comprehensive coverage of GenAI applications in data analysis, from preparation to predictive modeling.
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Practical focus with hands-on exercises and the option to bring personal datasets.
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Addresses ethical considerations and data privacy aspects relevant to AI implementation.
• unique insights
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Detailed explanation of GenAI's role in enhancing Microsoft Excel functionalities for data analysis.
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Exploration of AI agents and Microsoft Copilot Studio for workflow integration.
• practical applications
Participants will gain practical skills to improve data analysis efficiency using GenAI, automate tasks, and derive deeper insights from data, making them more effective in data-driven decision-making.
• key topics
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Generative AI (GenAI) for Data Analysis
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Data Preparation, Cleaning, and Integration
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Predictive Analytics and Data Visualization
• key insights
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Practical application of GenAI to enhance existing tools like Microsoft Excel.
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Focus on developing AI-gestützte Dashboards and efficient data analysis workflows.
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Guidance on integrating AI agents and understanding ethical implications.
• learning outcomes
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Understand the foundational principles and potential of Generative AI in data analysis.
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Gain practical experience using AI tools for data analysis, cleaning, and visualization.
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Develop the ability to integrate GenAI into personal and professional work processes for enhanced efficiency and insight generation.
Delving deeper into the practical aspects, this section outlines the core principles of conducting data analysis with the assistance of AI. It provides an overview of how GenAI can be utilized across various stages of the data lifecycle, including data visualization, preparation, cleaning, and predictive analytics. A significant focus will be placed on how GenAI can act as a catalyst for more efficient work within familiar environments like Microsoft Excel, enabling tasks such as table linking and macro creation. For those in more specialized roles, the application of GenAI in Data Science will be discussed, covering AI-supported forecasting, classification, and cluster analyses. Participants will learn to analyze and interpret datasets more effectively with GenAI's support, gaining a comprehensive understanding of its utility in extracting meaningful information.
“ Tools and Technologies for GenAI Data Analysis
Moving beyond the fundamentals, this section explores the more advanced capabilities of Generative AI in data analysis. It will cover sophisticated applications such as developing predictive models and engaging in scenario planning, allowing for more robust forecasting and strategic decision-making. Participants will learn how GenAI can be employed to generate data-based forecasts with a high degree of accuracy. Furthermore, the section will focus on the power of AI in visualizing complex relationships within datasets, making intricate information more accessible and understandable. These advanced techniques empower users to unlock deeper insights and drive more sophisticated analytical outcomes.
“ Practical Learning Environment and Benefits
The training program is delivered by experienced professionals, with instructors like Dennis Bogen and Raphael Wallsberger leading the sessions. The pedagogical approach emphasizes a blend of theory and practice, ensuring that each theoretical block is complemented by hands-on exercises. Participants are encouraged to bring their own datasets to apply learned concepts in real-world scenarios during the seminar. The learning experience is further enriched through group work and discussions, fostering a collaborative environment for idea exchange and problem-solving. This methodology ensures that participants not only grasp the concepts but also develop practical proficiency.
“ Target Audience and Skill Certification
This section provides essential logistical information for prospective participants. The training is offered at a price of €740,- (plus VAT) and spans 6 hours, with four scheduled online dates: June 12, 2026; September 17, 2026; December 14, 2026; and February 16, 2027. Participants have the option to reserve a spot without obligation. For organizations seeking tailored training solutions, the program is also available as an inhouse training, which can be customized to meet specific company needs and delivered either on-site or online, saving time and travel costs. Information on booking and available dates is readily accessible.
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