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Introduction to Data Science with Python – Online Course

Veranstaltungsdaten

13. October 2021 09:00 – 13. October 2021 17:00
14. October 2021 09:00 – 14. October 2021 17:00

Online

This Python training with a focus on data science is the ideal introduction to exploratory data analysis with Python. In multiple exercises, the course will familiarize participants with the different object types in Python. The core part of this course is the usage of pandas DataFrames to store data from different sources (e.g., CSV files) and to explore them via graphics and descriptive statistics.

Intended Learning Outcomes

At the end of the course, you will be able to

  • access elements from lists, dictionaries, and pandas DataFrames;
  • transform pandas DataFrames by changing, creating, or dropping columns;
  • read CSV datasets into Python and explore them via pandas, numpy, and seaborn;
  • iterate over each element from a list or a collection of lists;
  • write functions for simple arithmetic transformations of numeric inputs.

Didactic Methods

Joint programming with the trainer and all participants; practical exercises for each topic

Requirements

The course will take place remotely. Please install the Anaconda distribution with a recent version of Python (at least version 3.7) and Spyder on your computer before the course begins.

To participate in the online course, you need a PC/laptop with a current browser (recommended: Chrome or Firefox) as well as a headset (or speakers and a microphone), a webcam, and a stable Internet connection.

Proficiency in English at the B2 level of competency is required.

Dates

October 13, 2021, 9 am–5 pm, and
October 14, 2021, 9 am–5 pm

Target group

Doctoral candidates and postdocs from all disciplines

Modalities

Maximum number of 12 participants
Internal 50 EUR
External 150 EUR

Registration

Please register until  September 28, 2021 using the online registration form.

Lecturers

Christoph Schmidt, www.eoda.de

Event Organizer

MArburg University Research Academy (MARA)
Doctoral Program for Life and Natural Sciences

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