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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
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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