Who should attend
Senior managers and executives who aim to implement data-driven decision processes in their teams, and who wish to understand the principles of analytics or to acquire the knowledge and communication skills needed to steer their analysts. The course is also tailored for managers confronted with a specific analytics challenge who are expected to come up with concrete proposals on how to distill and extract value from data.
The program does not require any prior knowledge of coding or quantitative methods, although basic experience with Microsoft Excel would be helpful.
About the course
Have you ever looked at your company’s data and wondered how you could use it to add value to your business? Do you read the quarterly report from your data-science team wishing you had the confidence to turn its insights into optimal decisions? Do you want to learn how data analytics can optimize processes and drive evidence-based decision making?
If you answered yes to any of these questions, you will benefit from this program. With ever more access to data, managerial decision-making is increasingly data-driven. This program focuses on building the thinking skills necessary to become an informed and empowered user of analytics.
The program is delivered online and consists of up to 4 modules à 6-8 hours of self-paced learning, with one introductory module and three further in-depth modules. Each module can be booked individually – you can fully customize your learning journey according to your interests, requirements, and prior knowledge of the topic. Modules start in intervals of two weeks, but you can of course complete the course at your own pace.
Each of the modules has a synchronous online kick-off event and is further complemented by optional and individual synchronous online meetings with the lecturers. In these coaching sessions you are invited to present your own dataset or business challenge, and get expert advice from our lecturers. You will also be able to attend synchronous online keynotes with startup entrepreneurs or practitioners from large corporations, which explore best practices in the implementation of analytics tools in specific corporate contexts.
- Selecting the most relevant modules for your daily needs
- Getting acquainted with standard software packages
- Gaining a better understanding of how your analytics challenges can be operationalized and resolved
Each of the four modules consists of e-learning sessions, including individual exercises, case studies, video tutorials, moderated discussions in peer groups, synchronous webinars, and individual coaching sessions with our data experts.
Module 1: Analytics Fundamentals
- Risk, uncertainty, and errors
- Data as a guide to the unknown
- Descriptive analytics: Key indicators
- Predictive analytics: Model building
Module 2: Advanced Analytics
- Knowing your customers: segmentation models
- Keeping your customers (happy): churn models
- From predictive to prescriptive analytics
Module 3: Decision Trees and Risk Analysis
- Decision trees and decision-making under uncertainty
- Sensitivity analysis and risk profile
- Basics of Monte Carlo simulation
- Entropy and information gains
Module 4: Machine Learning & Artificial Intelligence
- Fundamentals of machine learning
- Random forests and neural networks
- Preparing high-quality data and optimizing models
Christoph Burger is senior lecturer and senior associate dean executive education at the European School of Management and Technology. Before joining ESMT, he worked five years in industry at Otto Versand and as vice president at the Bertelsmann Buch AG, five years at consulting practice Arthur D...
Catalina is the dean of faculty, professor of management science, and the first holder of the Deutsche Post DHL Chair. She joined ESMT European School of Management and Technology in November 2009 as an associate professor and served as the director of research between September 2010 and October ...
Before joining ESMT Berlin, Jens Weinmann was project manager of the Market Model Electric Mobility, a research project financed by the German environmental ministry (BMU). From 2007 to 2009, he worked as manager at the economic consultancy ESMT Competition Analysis. Further consulting experience...
Jan Nimczik joined ESMT Berlin in 2019 as an assistant professor of economics. Previously he worked as a PostDoc at the Humboldt University, Berlin. Jan obtained his PhD in Economics at the University of Mannheim. During his studies, he visited the University of California, Berkeley and the Unive...
Videos and materials
Read more about Business Analytics
Read more about Entrepreneurship
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.