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Natural Language Preprocessing Using spaCy
R
Riad Almadani
7/7/2025
·
1 min read
Course Overview
Course Title:
Natural Language Preprocessing Using spaCy
Instructor:
Riad Almadani
Target Audience:
Aspiring data scientists
Machine learning engineers
Software developers
Analysts and researchers
Prerequisites:
Python basics
Passion for learning
Curriculum Highlights
Key Topics Covered:
Introduction to NLP and Spacy
Working with Text Data
Tokenization and Part-of-Speech Tagging
How to use spaCy models
Rule-based matching
Tokenization
Part-of-speech tagging
Named entity recognition
Dependency parsing
Text classification
Key Skills Learned:
Gain a solid understanding of linguistic concepts
Explore tokenization
Part-of-speech tagging
Named entity recognition
Dive into dependency parsing
Text classification
Build practical NLP applications using spaCy
Course Format
Duration:
6 hours on-demand video
Format:
Self-paced online course
Resources:
Access on mobile and TV
Certificate of completion
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