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Analytics for Decision Makers

  • USD 545

  • online
  • Online |
  • Oct, 10th 2022 - Oct, 21st 2022
    • Certificate

    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. 

    Program Benefits

    • Cherry-pick the tools and techniques that are most relevant for your daily business practice thanks to the multi-modular structure of the program
    • Get acquainted with standard software packages that allow you to prepare and manage data inputs, generate and interpret results, and draw the right conclusions
    • Obtain a better understanding of how your analytics challenges can be operationalized and resolved.   

    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.

    Faculty

    Christoph Burger
    Senior Lecturer, ESMT Berlin
    Jens Weinmann
    Program Director, ESMT Berlin
    Catalina Stefanescu-Cuntze
    Professor of Management Science and Deutsche Post DHL Chair, ESMT Berlin
    Jan Nimczik
    Assistant Professor of Economics, ESMT Berlin

    *Program faculty is subject to change

    Curriculum

    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

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