Overview

The learning goals of the course can be summarised in the following points:

install and run Python and all other needed external packages

write basic python code, including conditional statements, loops and functions

import and export data in python

analyze different types of data in python using the pandas package

create meaningful visualizations in python to summarize different types of data using Matplotlib and seaboarn packages

Effectively and clearly present analytical results, i.e. data storytelling

Programme Structure

Main course components:In this course, we will cover the following regarding Python as a tool for data analysis and visualization:

Data types and compound data structures

Conditional statements and loops

Python functions

Visualizing data using Matplotlib and Seaborn

Importing, exporting and analyze different types of data using pandas

Bonus: creating interactive plots with Plotly

The main learning tools will be:

Python jupyter notebooks and .py files shared in class by the instructor

Recommended educational material including online ebooks, blog posts, web-based tutorials and videos. All such materials are free for educational use and will be shared with the students via email and in class

Recommended books and online courses (not free and these will be optional)

Students are assumed to have their own personal laptops with a Python installation as the main hardware tool required for this course

Lecturers

Dina Deifallah

Key information

Duration

Full-time
- 14 days

Start dates & application deadlines

Starting 2026-01-07 00:00:00
- Apply before 2025-12-10 00:00:00

Language

English

TOEFL^® IBT

87

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Credits

3 ECTS

Delivered

On Campus

Disciplines

Electrical Engineering Mathematics General Engineering & Technology View 19 other Short Courses in General Engineering & Technology in Germany

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Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

TOEFL^® IBT

87

Schedule TOEFL®

Student insurance

Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:

Additional medical costs (i.e. dental)
Repatriation, if something happens to you or your family
Liability
Home contents and baggage
Accidents
Legal aid

We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.

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Starting from €0.53/day, free cancellation any time.

Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at TU Berlin and/or in Germany, please visit Student Insurance Portal.

Other requirements

General requirements

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.

Some basic programming knowledge, but not necessarily in python, is recommended for this course.Students are assumed to have their own personal laptops with a Python installation as the main hardware tool required for this course.

Tuition Fee

To always see correct tuition fees

International

1050 EUR/full

Tuition Fee

Based on the tuition of 1050 EUR for the full programme during 14 days.
EU/EEA

1050 EUR/full

Tuition Fee

Based on the tuition of 1050 EUR for the full programme during 14 days.

Working professional/Non-student: 1250 Euro

Living costs for Berlin

836 - 1340 EUR /month

Living costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

Funding

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Python for Data Analysis and Visualization TU Berlin

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