Success Exam | Python NLTK : Natural Language ToolKit | NLP

Course Overview

• Course Title: Success Exam | Python NLTK : Natural Language ToolKit | NLP
• Instructor: Faisal Zamir
• Target Audience:
  • Learners interested in Natural Language Processing (NLP)
  • Python developers
  • Students and professionals seeking to master NLTK
• Prerequisites:
  • Basic understanding of Python

Curriculum Highlights

• Key Topics Covered:
  • Introduction to NLP and NLTK
  • Understanding NLTK in Python
  • Core NLP Techniques with NLTK
  • Practical Implementations with NLTK
  • Advanced NLTK Concepts
  • NLP vs. NLTK: Understanding the Difference
• Key Skills Learned:
  • Tokenization and its importance in NLP tasks
  • Stemming and its real-world applications
  • Part-of-Speech (POS) tagging for better linguistic analysis
  • Sentence tokenization using NLTK
  • Sentiment analysis with NLTK tools
  • Named Entity Recognition (NER) implementation
  • Syntactic parsing and semantic analysis with WordNet
  • Text summarization projects using NLTK

Course Format

• Duration: N/A
• Format: Self-paced online course
• Resources:
  • 4 practice tests
  • Access on mobile
  • Quizzes and assessments