By the end of this course, learners will be able to explain core Natural Language Processing (NLP) concepts, preprocess and normalize textual data, extract meaningful features, and apply machine learning algorithms to solve real-world language-based problems.

Apply Natural Language Processing Techniques in Python
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Empfohlene Erfahrung
Was Sie lernen werden
Explain core NLP concepts and preprocess text using tokenization, normalization, stemming, and lemmatization.
Extract meaningful textual features and prepare data for machine learning models.
Apply NLP techniques and ML algorithms to solve real-world language-based problems.
Kompetenzen, die Sie erwerben
- Kategorie: Predictive Analytics
- Kategorie: Applied Machine Learning
- Kategorie: Unstructured Data
- Kategorie: Feature Engineering
- Kategorie: Data Transformation
Wichtige Details

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Januar 2026
6 Aufgaben
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In diesem Kurs gibt es 2 Module
This module introduces the fundamental concepts of Natural Language Processing (NLP), covering the nature of human language data, core NLP terminology, essential preprocessing techniques, and the setup of an NLP development environment to support practical experimentation.
Das ist alles enthalten
6 Videos3 Aufgaben
This module focuses on advanced text preprocessing workflows, including tokenization, stopword removal, stemming, and lemmatization, and concludes with the integration of machine learning algorithms for building effective NLP models.
Das ist alles enthalten
6 Videos3 Aufgaben
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