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Vom Excel-Nutzer Zum Data Scientist: Python, Machine Learning & Production - Der Vollständige Lernpfad
Paperback
DatabasesGeneral ComputersProbability & Statistics
ISBN13: 9783658524876
Publisher: Springer Vieweg
Published: Oct 30 2026
Pages: 930
Language: German
Dieses Buch bietet einen praxisorientierten Leitfaden für den Übergang von klassischer Excel-Analyse zu professioneller Data Science mit Python und SQL. Anstatt trockener Theorie vermittelt es tiefgehendes Verständnis durch reale Business-Szenarien und die Avatar-Methode, bei der echte Erfolge und spektakuläre Fehler als didaktische Anker dienen. Das Werk adressiert das Kernproblem vieler Analysten: die Grenzen manueller Workflows in puncto Reproduzierbarkeit, Skalierung und Fehleranfälligkeit. Die Hauptthemen erstrecken sich über den gesamten Data-Science-Lifecycle: von robustem Python-Code und fortgeschrittener SQL-Mastery über Data Warehousing und explorative Datenanalyse (EDA) bis hin zu Machine Learning, NLP und MLOps in der Cloud.
Leser lernen nicht nur, Modelle zu bauen, sondern diese auch durch Testing, Logging und Docker-Containerisierung produktionsreif zu gestalten. Die Relevanz liegt in der direkten Anwendbarkeit: Jedes Kapitel kombiniert erklärendes Storytelling mit ca. 40 % praxiserprobtem Code, der sofort in echten Projekten eingesetzt werden kann. Das Buch löst das Problem der Notebook-Sackgasse, indem es zeigt, wie aus isolierten Analysen skalierbare, automatisierte Pipelines entstehen. Dieses Buch richtet sich an Business Analysts, Datenspezialisten und angehende Data Scientists, die den nächsten Karriereschritt gehen und ihre analytischen Fähigkeiten auf ein professionelles, engineering-nahes Niveau heben möchten.
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