Berlin, Germany

Introduction to Python for Data Analysis

online course
when 17 August 2020 - 28 August 2020
language English
duration 2 weeks
credits 3 EC
fee EUR 700

This program is a beginners’ Python course where participants will gain a full understanding of how to program in Python and how to use Python for data analysis and visualization.

The course covers two parts: Python programming and Python in data analysis. In the first part, you will learn about Python programming fundamentals (data type, loop, if-conditions, etc.) and improvements (function, class, modules). In the second part, you will learn to use the most popular Python modules for data analysis: numpy, pandas, matplotlib. Examples and small projects will be applied for practice in every unit. Additionally, some basic skills and tools on crawling (requests, beautiful soup, re) will also be introduced.

This course will not include the topic of machine learning.

Course leader

Dongrui Jiang is a Research Assistant in the Energy & Resource Management Department of the TU Berlin and an engineering Ph.D. student, specializing in numerical simulation technologies. She uses Python as a working language in her scientific research.

Target group

Open for all disciplines.

Course aim

- Learn basic Python programming with examples
- Know how to modularize your code with function, class and module
- Learn to install and run a third-party Python library using pip
- Use common Python tools for data analysis and visualization
- Know basic knowledge to crawl data online

Credits info

3 EC
"We will ask participants to fulfill the following technical requirements:
• Fully functional device (laptop, tablet, PC)
• Stable internet connection
• Software: Zoom (App installed on desktop or over browser. Participants are requested to use their real names as zoom account names.)
• Recommended: external headset for better sound quality"

Fee info

EUR 700: Aug. 10-17: *Reading week* : flexible, 5 hours preparatory work to be done on-demand
Aug. 17-21: Week 1: Live and on-demand course elements
Aug. 24-28: Week 2: Live and on-demand course elements

The fee covers the course, course materials, and a digital cultural program.

Scholarships

no