Data Analytics
Certificate Course - Management & Leadership - MM_MSc.1.3.I26
| Date | Oct 13-14, 2026 |
| Duration | 1,5 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | upon request |
| Cost | 1,290 € |
Fundamentals
Learn the core principles of data analytics, including data exploration, cleaning, preparation, and systematic methods for extracting meaningful information.
Technology
Work with tools and techniques for data ingestion, analysis, and visualization to transform raw datasets into actionable insights.
Applications
Apply analytics to real-world datasets to uncover patterns, support evidence-based decisions, and generate knowledge for practical business and organizational challenges.
What you'll explore
- Understand the data science life cycle and the key stages involved in transforming raw data into actionable insights.
- Apply data analytics as a systematic approach to exploring, preparing, analyzing, and interpreting real-world datasets.
- Utilize statistical learning and machine learning methods to discover patterns, build predictive models, and support decision-making.
- Implement current data analytics models and algorithms using industry-standard tools such as Python, NumPy, and scikit-learn.
- Gain practical experience through hands-on exercises that apply analytical techniques to real-world data and business problems.
- Evaluate analytical results and communicate findings effectively through data-driven reasoning and visualization techniques.
Your key takeaways
- Evaluate real-world datasets using a systematic data analytics approach to extract meaningful information and actionable insights;
- Gain a thorough understanding of the fundamental principles of data analytics, machine learning, and the data science life cycle;
- Apply industry-standard tools, including Python, NumPy, and scikit-learn, to analyze, model, and visualize data;
- Assess and implement modern machine learning models and algorithms to solve practical analytical problems;
- Develop the ability to transform raw data into knowledge that supports evidence-based decision making.
Taught by recognized experts in Data Analytics
Benefit from the knowledge of leading specialists with extensive experience in research and industry. Their deep expertise guarantees a course of outstanding academic and practical quality.
Dr.-Ing. Katharina Glock
Dr.-Ing. Katharina Glock is a researcher at the Karlsruhe Institute of Technology (KIT) specializing in operations research, logistics, and data-driven decision-making. Her work focuses on optimizing complex systems such as mobility, transport, and emergency response through mathematical modeling, simulation, and AI-supported analytics. She develops innovative solutions that enhance efficiency, robustness, and sustainability in logistics networks. By combining advanced optimization methods with real-world applications, she contributes to smarter, more resilient systems for future mobility and infrastructure planning.
Dr.-Ing. Fabian Rigoll
Dr.-Ing. Fabian Rigoll is Head of the Information Process Engineering research division at the FZI Research Center for Information Technology. He studied Industrial Engineering at Karlsruhe Institute of Technology (KIT) and earned his doctorate with a focus on user-centered energy data management, addressing privacy and data protection in energy informatics. His research experience spans national and international projects in energy data systems and intelligent technical communication. Since 2017, he has led research teams at FZI, focusing on intelligent information processing in complex systems. Today, he drives interdisciplinary innovation at the intersection of data, systems engineering, and applied informatics.
Who should attend
This course is particularly beneficial for professionals in the following fields
- Data analytics and business intelligence professionals
Data analysts, business intelligence specialists, and reporting professionals seeking to strengthen their analytical skills and derive actionable insights from data. - Business and management professionals
Managers, consultants, and decision-makers who want to leverage data analytics and machine learning to support strategic planning and evidence-based decision making. - IT and technology professionals
Software developers, data engineers, and IT specialists interested in applying modern analytical methods, machine learning models, and data-driven approaches to real-world problems. - Researchers and quantitative professionals
Professionals working with empirical data in research, economics, social sciences, engineering, or related fields who seek practical skills in data analysis and predictive modeling. - Professionals transitioning into data-driven roles
Individuals looking to develop foundational competencies in data analytics, machine learning, and the use of industry-standard tools such as Python, NumPy, and scikit-learn. - Early-career professionals and students
Graduates, PhD candidates, and academic staff who wish to build practical experience in data analytics and machine learning through hands-on work with real-world datasets.
Advance your career with KIT-level expertise
Benefit from the reputation of the Karlsruhe Institute of Technology (KIT) while gaining practical skills, flexible learning opportunities, and a recognized certificate to support your long-term professional growth.
Flexibility
Gain focused expertise in a specific field without committing to a full degree program, allowing you to build relevant knowledge efficiently and integrate learning seamlessly into your professional routine.
Relevance
Benefit from high-quality academic content combined with practical insights, delivered by experienced experts, supporting continuous, lifelong learning while ensuring direct applicability in real-world scenarios.
Advancement
Enhance your professional profile with a recognized certificate, demonstrating your commitment to ongoing development and supporting your career with tangible, verifiable credentials.