AI and Data-Driven Analysis

Course overview

Objective The training provides knowledge and practical skills in the field of Artificial Intelligence (AI) and automation. It covers the fundamentals of AI technologies, their application in process automation, and the use of AI for data analysis. The goal is to enable the implementation and use of AI-based solutions to enhance efficiency and promote innovation in work processes. Content The training is divided into two main areas: AI and Automation, and AI-Driven Data Analysis. In the area of AI and Automation, the fundamentals and historical development of AI and automation are discussed. Participants will learn key technologies and basic concepts, including how Make.com works for automation tasks. Focus areas include data management, workflow documentation, troubleshooting, and report automation. The role of data as the foundation for AI systems and the implementation of AI solutions in practice are also covered. An excursion into Large Language Models (LLMs) and the application of AI in process automation rounds off this part. Case studies and best practices provide application-oriented knowledge. The training concludes with a final project and a look at future trends and innovations in AI and automation. The area of AI-Driven Data Analysis focuses on extracting insights from data using AI. Content includes the use of AI analysis dashboards and co-pilots, data preparation and visualization, as well as code automation with tools like GitHub Copilot. Participants will learn to create an AI analysis pipeline from raw data to business strategy. Fundamentals of machine learning, including supervised and unsupervised learning, will be covered. Participants will learn to build their own AI engines with tools like Knime and conduct final projects. Additional topics include data cleaning, deep learning in data analysis, feature engineering, dimensionality reduction, model evaluation, and interpretability of AI models. Ethics and data protection in AI-driven data analysis, as well as the use of AI analysis tools, will also be addressed. A practical project for implementing AI-driven data analysis serves to apply what has been learned. Learning Objectives Upon completion of the training, participants will be able to: - Understand and explain the fundamentals of AI and automation. - Use automation tools like Make.com for process optimization. - Document workflows, troubleshoot issues, and automate reports. - Evaluate the role of data for AI systems. - Implement AI solutions in practice. - Understand how Large Language Models (LLMs) work. - Apply AI for process automation. - Identify data patterns through AI-driven analyses. - Utilize AI analysis dashboards and co-pilots. - Prepare and visualize data for analysis. - Apply concepts of machine learning. - Develop and evaluate their own AI models. - Use AI-driven analysis tools. - Implement AI-driven data analyses in practical projects. Career Prospects The knowledge and skills acquired are relevant for ac…

Upcoming dates

• 2026-12-20T23:00:00.000Z · 2027-02-11T23:00:00.000Z · Berlin · Combined Learning
• 2026-12-20T23:00:00.000Z · 2027-02-11T23:00:00.000Z · Bielefeld · Combined Learning
• 2026-12-20T23:00:00.000Z · 2027-04-08T22:00:00.000Z · Bielefeld · Combined Learning
• 2026-12-20T23:00:00.000Z · 2027-04-08T22:00:00.000Z · Bremen · Combined Learning
• 2026-12-20T23:00:00.000Z · 2027-02-11T23:00:00.000Z · Bremen · Combined Learning