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VERSION:2.0
PRODID:https://github.com/derhansen/sf_event_mgt
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BEGIN:VEVENT
UID:4794-409@gi.de
CLASS: PUBLIC
SUMMARY:Python Basics for Data Analysis (English)
DESCRIPTION:Course duration: 4 half days, each from 09:00 - 12:15 CET (Onli
 ne-Live-Seminar)\n\nCourse language: English (we can switch to German if al
 l participants are fluent in German)\n\nThe Python Basics course is intende
 d for participants who want to learn basic Python skills as well as efficie
 nt handling of data preparation, data processing, and data analysis in Pyth
 on. In addition, general "best practices" in Python will be taught, includi
 ng, writing simple, readable, and modularly extensible code. All topics pre
 sented will be explained, demonstrated, and practiced in detail with the he
 lp of participant exercises under intensive instruction. The course covers 
 the following topics:\n\nPart 1: Introduction to Python\n\n- Introduction t
 o the basics of Python\n\n- Installation and use of Python and useful Pytho
 n modules\n\n- Creating and working with virtual environments\n\n- Explanat
 ion of the most important data types, operators, functions, and help pages\
 n\n- Introduction to NumPy and Pandas\n\n- Importing and exporting data\n\n
 - Working with DataFrames and vectors (numeric, logical, character, factors
 ), e.g. indexing, splitting, and transforming variables or data sets\n\n- C
 alculating statistical ratios (e.g.: mean, quantiles, variance, etc.)\n\nPa
 rt 2: Data Wrangling in Python\n\n- Review of Python basics: built-in struc
 tures, NumPy, IPython, jupyter notebook, package management, jupytext\n\n- 
 Series and DataFrames: generation, meaning of line index, filtering, pointe
 r vs. copy\n\n- Importing and exporting data from text files and (unstructu
 red) Excel spreadsheets, and accessing databases using Python\n\n- Data cle
 ansing: Handling missing values, editing strings, removing duplicates.\n\n-
  Transforming data by vectorized operations like map or apply\n\n- Merging 
 different data sources and creating a "good" table structure of the data\n\
 n- Grouping of data and aggregations: Split-Apply-Combine\n\n- Time series 
 and date-time objects\n\nPrerequisites: none\n\nFor registrations 3 months 
 before the course starts, you can get an additional 10% discount on top of 
 the earlybird price using the following promotion code: GI
LOCATION:Zoom (Online)
DTSTAMP:20220314T105840Z
DTSTART:20220927T070000Z
DTEND:20220930T101500Z
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