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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D">Hallo liebe Python-User,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D">wir sind ein Unternehmen, das in Nürnberg Schulungen für Firmen organisiert und verkauft. Über einen „Kollegen“ von Ihnen bin ich auf Ihre Plattform aufmerksam
geworden.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D">Ich suche für folgende Schulung einen Trainer:<o:p></o:p></span></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">Python for Data Science<o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">Zwischen 7 und 12 Data Scientists und Entwickler.<o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">7-12 Pers.<o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">Dauer: 2 Tage; 09.00h – 16.30h<o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">Terminrahmen: KW 31-37.<o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">Sprache: englisch<o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:115%;font-family:"Arial","sans-serif"">Ort: Nürnberg<o:p></o:p></span></i></p>
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<p class="MsoNormal" style="line-height:105%"><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Fokus des Kurses ist es wichtige Elemente von Python 3, sowie eine Reihe von Modulen mit Relevanz für Data Science Aufgaben kennen
zu lernen. Der Kurs soll im Wesentlichen aus praktische Übungen (z.B. in Jupyter Notebooks) bestehen. Grundkenntnisse in Python können vorausgesetzt werden. Thema sollte sein:<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:105%"><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif""><o:p> </o:p></span></i></p>
<p class="MsoNormal" style="line-height:105%"><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Wichtige Aspekte von Python 3
<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Listen, Dictonaries und Sets und die damit verbundene comprehension
<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Klassen und Module<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Iteratoren, Generatoren und Context Manager<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span lang="EN-US" style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Exceptions<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span lang="EN-US" style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Unit Tests (am liebsten pytest)<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:105%"><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif""><o:p> </o:p></span></i></p>
<p class="MsoNormal" style="line-height:105%"><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Der Python Data Science Stack<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span lang="EN-US" style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">numpy, vor allem
<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span lang="EN-US" style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Überblick über ndarray
<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span lang="EN-US" style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span lang="EN-US" style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Copy vs. View<o:p></o:p></span></i></p>
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</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Erstellung, Manipulation und wichtige Operationen von ndarraya<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Lineare Algebra<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">scipy<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">insbesondere scipy.stats und scipy.optimize
<o:p></o:p></span></i></p>
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</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">pandas<o:p></o:p></span></i></p>
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</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">I/O via pandas<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Series und DataFrames<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Selektion und Indexing<o:p></o:p></span></i></p>
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</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Joins<o:p></o:p></span></i></p>
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</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Wichtige eingebaute Funktionen, z.B. Statistiken<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Anwendung von Funktionen (auf Tabellen, Zeilen, Spalten) und Aggregationen<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Index über Zeitstempeln, d.h. Verarbeitung von Zeitreihen
<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:105%"><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif""><o:p> </o:p></span></i></p>
<p class="MsoNormal" style="line-height:105%"><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Visualisierung
<o:p></o:p></span></i></p>
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</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Wesentliche Funktionen zur Visualisierung in pandas<o:p></o:p></span></i></p>
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<span style="font-size:9.0pt;line-height:105%;font-family:Wingdings">§</span><span style="font-size:7.0pt;line-height:105%;font-family:"Times New Roman","serif"">
</span><i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif"">Des Weiternen Überblich über min. ein weiteres Visualisierung-Paket, z.B. Seaborn oder ggpy <o:p></o:p></span></i></p>
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<i><span style="font-size:9.0pt;line-height:105%;font-family:"Arial","sans-serif""><o:p> </o:p></span></i></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D;mso-fareast-language:DE">Sabine Grüner<o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:7.0pt;font-family:"Verdana","sans-serif";color:#1F497D;mso-fareast-language:DE">Schwabacher Str. 3, 90439 Nürnberg<o:p></o:p></span></p>
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<p class="MsoNormal"><b><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:red;mso-fareast-language:DE">Seminare 2017:
</span></b><span style="color:#1F497D;mso-fareast-language:DE"><a href="http://www.celecta.de/"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D;text-decoration:none">www.celecta.de</span></a></span><span style="font-size:8.0pt;font-family:"Verdana","sans-serif";color:#1F497D;mso-fareast-language:DE"><o:p></o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:red;mso-fareast-language:DE">ADA-Kurse 2017:</span></b><span style="font-size:8.0pt;font-family:"Verdana","sans-serif";color:red;mso-fareast-language:DE">
</span><span style="color:#1F497D;mso-fareast-language:DE"><a href="http://www.ada-schein-nürnberg.de/"><span style="font-size:10.0pt;font-family:"Verdana","sans-serif";color:#1F497D;text-decoration:none">www.ada-schein-nürnberg.de</span></a></span><u><span style="font-size:10.0pt;color:#1F497D;mso-fareast-language:DE"><o:p></o:p></span></u></p>
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<p class="MsoNormal"><span style="font-size:7.0pt;font-family:"Verdana","sans-serif";color:#1F497D;mso-fareast-language:DE">Geschäftsführung: Dipl.-Kffr. Rita Kolaya, Dipl.-Psych. Sabine Grüner, Dipl.-Kfm. Stefan Mänzel<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:7.0pt;font-family:"Verdana","sans-serif";color:#1F497D;mso-fareast-language:DE">Sitz der Gesellschaft: Nürnberg, Amtsgericht Nürnberg HRB 19380<o:p></o:p></span></p>
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