Logo of TU Berlin Summer & Winter University

Winter SchoolPython for Data Analysis and Visualization

Tuition fee €890 per programme

The program price consists of the course/tuition fee (student or working professional, see details below) plus the registration fee (€60).

Student course/tuition fee: €890
Working professional course/tuition fee: €1080

This course/tuition fee covers the course, course materials and a cultural program.

Registration fee €60 one-time

The registration fee is in addition to the course/tuition fee and covers the processing of your application. It is payable upon registration. Please note that the registration fee is non-refundable.

More information

tu-berlin.de/summer_university 

Overview

According to the 2022 annual IEEE Spectrum survey of the top programming languages, Python remains the most popular programming language in job listings. In this
course, the fundamentals of Python are covered, with a special focus on the skills necessary for
in-depth data analyses and data visualization. These two skills are fundamental in a wide range
of disciplines, including but not limited to STEM (Sciences, Technology, Engineering and
Mathematics) and Humanities fields of study.

In this course, we will cover the following:

1. Data types and compound data structures
2. Conditional statements and loops
3. Python functions
4. Importing, exporting and analyze different types of data using pandas
5. Visualizing data using Matplotlib and Seaborn
6. Bonus: developing dashboards using Metabase

At the end of the two weeks course, students will work and present a final personal data
analytics and visualization project.

Learning goals

In this course, the fundamentals of Python are covered, with a special focus on the skills
necessary for in-depth data analyses and data visualization. These skills are fundamental in a
wide range of disciplines, including but not limited to STEM (Sciences, Technology, Engineering
and Mathematics) and Humanities fields of study.

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

1. install and run Python and all other needed external packages
2. write basic python code, including conditional statements, loops and functions
3. import and export data in python
4. analyze different types of data in python using the pandas package
5. create meaningful visualizations in python to summarize different types of data usingMatplotlib and seaboarn packages
6. Effectively and clearly present analytical results, i.e. data storytelling

Main course components

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

1. Data types and compound data structures
2. Conditional statements and loops
3. Python functions
4. Visualizing data using Matplotlib and Seaborn
5. Importing, exporting and analyze different types of data using pandas
6. Bonus: developing dashboards using Metabase

The main learning tools will be:

1. Python jupyter notebooks and .py files shared in class by the instructor
2. 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
3. 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.

Apply now! Winter Term 2 2023
Application deadline
19 Dec 2022, 23:59:59
Central European Time
Studies commence
16 Jan 2023
Apply now! Winter Term 2 2023
Application deadline
19 Dec 2022, 23:59:59
Central European Time
Studies commence
16 Jan 2023