- Prof. Dr. Martin Huber, University of Fribourg
Data Analytics & Machine Learning for Managers: 7th- 8th November 2023
What to expect
- Non-technical but informative introduction to data analytics and machine learning for data driven
analysis of business processes (like customer behavior, production, turnover…) - Data visualization and descriptive statistics (e.g. the average or variability of prices)
- Regression: analyzing associations between business factors (like marketing and sales)
- Intuition of machine learning for optimally forecasting future business outcomes (e.g.sales),
based on information in past data (e.g. price, quality, competition) - Important concepts of machine learning: alternative algorithms (e.g. decision trees,
random forests, lasso, boosting…), performance assessment, and tuning of algorithms - Business cases and practical examples with real data using the no-code software “BigML”
Short course description
Understanding the diverse tools and objectives of data analytics and machine learning is key for proficiently analyzing data within companies and organizations. This course offers an introduction to essential statistical and machine learning techniques, enabling precise evaluations of the business environment and informed estimations and forecasts of businessrelevant factors, such as key performance indicators.
Competition Behaviors and Policies: 14th- 15th November 2023
What to expect
- Economic fundamentals of competition
■ Definition of the relevant markets
■ Economic basis of competition policy
- Firms behaviors fundamentals affecting competition
■ Horizontal agreements
■ Vertical restraints
■ Abuse of dominant position
■ Mergers and acquisitions
- Competition fundamentals in the digital economy
■ Competition patterns in digital networks and platforms (eg. Google)
■ Disruptive new market entrants of the sharing economy (eg. Uber, Airbnb)
Short course description
The course on Competition highlights the main economics basis of competition behaviors and developments with a strong emphasis on the Digital Economy features such as the price setting algorithms or the impact of the sharing economy on the markets (Uber, Airbnb, etc.). The course scrutinizes the competition patterns in digital markets as well as the competition patterns in digital networks and platforms. Participants will have to deal in class with real and current competition cases such as Apple Pay case and Google on line advertising case.
- Dr. Jean Binder – Author of “Global Project Management” book and Global Head of the Life Sciences PMO,Philip Morris International
- With participation of Sarianna Benain – Senior Project Portfolio Manager, SITA
Agility in Project Management: 21st- 24th November 2023
What to expect
In every course module you will have the opportunity to learn and practice traditional project management principles, agile practices and reflect on ways to leverage AI and Machine Learning to improve the project and portfolio forecasts and management at your company.
- Initiate – Get your project started and define your approach (traditional, agile or hybrid).
- Plan – Define your requirements, scope and prepare an agile backlog or a schedule and Gantt charts.
- Monitor – Establish metrics and use them to monitor the progress of your project or agile team
- Communicate – Understand communication challenges and agile techniques across country borders
- Organize – Select the best resources in the right locations to work in agile and self-organizing teams
- Collaborate – Establish trust and collaboration to benefit from multicultural global teams.
Short course description
In a very interactive course that can be directly applied at your company during an agile transformation or definition of a new project management method, we will discuss the challenges and benefits of Global Projects and Agile Approaches in light of AI & Machine Learning perspectives. You will get a practical insight into the latest trends in research and practice of project management and assess which principles can be applied in your companies to stay ahead in today’s competitive and global economy.
Impact Evaluation for Managers: 28th- 29th November 2023
What to expect
- Non-technical, but informative introduction to impact evaluation for assessing the effect of interventions (e.g. discounts) on business outcomes (e.g. sales) for decision support
- Different evaluation designs: 1) experiments (A/B testing); 2) “instrumental variable” designs for fixing “broken” experiments; 3) “selection-on-observables” designs based on groups with and without intervention that are similar in observed characteristics; 4) “difference-in-differences” designs based on groups with comparable time trends
of business outcomes; 5) “regression discontinuity” designs based on indices e.g. customer score) which determine the receipt of an intervention (e.g. fidelity card) - Machine learning-based impact evaluation for detecting and optimally targeting customer segments for which interventions are particularly effective (e.g. loyal customers)
- Business cases and practical examples with real data using graphical interfaces in web applications or the no-code software “BigML” – no programming required!
Short course description
For effective decision making, it is crucial to evaluate the consequences or impact of specific actions or policies, whether it’s the impact of pricing strategies on sales or of employee training on productivity. This course provides an introduction to cutting-edge data-driven impact evaluation
methods—a critical tool for supporting decision-making within companies and organizations.
Course modules 2024
- Generative AI for managers 18-19.01.2024
- Operationnal Excellence 13-14.02.203
- Privacy compliant data analytics 22-23.02.2024
- Strategic Leadership 19-20.03.2024
- Business Ethics 21-22.03.2024
- Machine learning within an organisation 23-24.04.2024
- The Art and Science of Negotiation 13-14.05.2024 (more information soon)
- Management Control Systems 13-14.06.2024
- Using Monte Carlo Simulations for enhanced decisionmaking 20-21.06.2024