Summer School
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System Dynamics and Data Science with Python
On-Campus:14.8 - 25.8.20233 ECTS

max. 24 participants
Registration Deadline: July 17th, 2023

Register now!


TU Berlin Summer & Winter School
+49 30 4472 0230


This course covers the theory, tools, and techniques associated with systems thinking approach which allows students to understand the relationship and connections between components of a system, instead of looking at the individual components one by one. Moreover, the course  contains the learning materials, practices and case studies to develop the knowledge and skills of the students in the field of data science and its application in the real business/work world. The students will learn how to apply analytical techniques and scientific principles to extract valuable information from business data for decision-making, strategic planning.

This program helps students to develop understanding and proficiency in system dynamics simulation to evaluate the future of one business in the real world by system thinking approach to consider the linear and nonlinear impacts between different components of one business.

Learning Goals & Syllabus

Learning Goals:

  • Systems Thinking and Business Dynamics
  • Learn the relevance of taking a wider system perspective in examining challenges and understand why decisions and responses change naturally over time
  • Learn to examine the possible impacts of policy changes and technological innovations on business environment
  • Tools for System Dynamics Modeling
  • Develop skills in the use of simple mapping and spreadsheets to elicit mental models of system structures, and be able to anticipate from their structures, the dynamic behavior of simple closed‐loop systems
  • Understanding statistical association and the difference between causation and correlation
  • Understanding and   developing the skills to apply descriptive techniques and Statistical inference in the real business cases, social and marketing studies
  • Machine Learning (ML) process, supervised vs unsupervised, validation approaches, over/ under fitting
  • Introduction to basic Clustering approaches
  • Introduction to basic Classification approaches

Main course components

  • Introduction of System Thinking Approach
  • Principles of Dynamic Modelling and Sustainable Policy Design
  • System Dynamics Simulation Software
  • System Dynamics Tools Part 1: Building a model with causal loop diagrams
  • System Dynamics Tools Part 2: Mapping the stock and flow structure of systems linking with feedback
  • Result analysis of System Dynamics Modeling
  • Principles of Python
  • Descriptive techniques
  • Linear Regression
  • Clustering
  • Overview of Machine Learning (ML) process, supervised vs unsupervised,
  • validation approaches, over/under fitting
  • K-means in the business context
  • Classification
  • Introduction to basic Classification approaches
  • KNN (k-nearest neighbors algorithm)


A detailed syllabus with information on the schedule will be made available to registered participants.
You may find the syllabus useful when discussing with your home university whether the ECTS credits attainable for this course are accepted by them.

Please note this is a full-time, intensive course and participants will be expected to attend lectures (18 hours of class per week) and complete independent study Monday through Friday. Additional study may also be required on weekends. The activities of the cultural program are also shown in the syllabus.

Target Audience

The Bachelor graduates and Master/PhD students of:

  • Business and Economics
  • Industrial, Civil, IT and Computer Science, Mechanical, Electronical Engineering
  • Urban planning
  • Transportation Engineering

Participants of the TU Berlin Summer School must meet the following requirements: (i) B2 level English, or equivalent and (ii) at least one year of university experience. Furthermore, students should know fundamentals of mathematics and statistics as taught in Bachelor programs. 


Dr. Hamid Mostofi is senior researcher since 2017  in faculty 1 of TU Berlin.

He worked in automotive industry, urban mobility and smart city research institutes from 2008. In TU Berlin, he had the role of project manager in SUMIC project “ Developing smart urban mobility, funded by BMBF (German Federal Ministry of Education and Research)in 2021, project team member of GECI ( Green Energy Center) funded by BMU (German Federal Ministry of Environment) between 2017 -2021). His current project is eHaul : Electrification of long haul heavy-duty commercial vehicles with automated battery swapping stations which is funded by German Federal Ministry for Economic Affairs and Climate Action.

In addition of his research activities, he is lecturer at TU Berlin since 2018 for modules Economics, and business model development  for the program MBA sustainable Energy/Mobility management, and at HTW Berlin since 2019 for the course “system dynamics modelling for business analysis”.

Course fees

Course fees for System Dynamics and Data Science with Python are as follows:

  • Student: 950 Euro
  • Working professional/Non-student: 1140 Euro

Please note that students will be required to upload proof of their student status (student card/ enrollment information) during the registration process.

Summer School On-Campus:14 August - 25 August, 20233 ECTS credit points