Master NLP fundamentals by building real projects using NLTK — tokenize, extract, generate, and analyze text with Python
This is one of the most hands-on and comprehensive courses ever built for Natural Language Processing (NLP) using the NLTK library in Python.
What you’ll learn
- Understand the core principles of Natural Language Processing (NLP) and how text data is processed, cleaned, and analyzed using Python..
- Master the NLTK library to perform tasks such as tokenization, POS tagging, chunking, named entity recognition, and syntactic analysis..
- Build hands-on NLP applications such as a Shakespeare-style text generator, resume skill extractor, and synonym-based sentence transformer using only NLTK..
- Analyze real-world text datasets by working with corpora, computing word frequencies, exploring author styles, and designing autocomplete-like features..
- Learn to extract structured information like names, dates, and entities using chunking, regular expressions, and grammar-based pattern matching..
Course Content
- Course Introduction & Setup –> 6 lectures • 13min.
- Text Preprocessing Essentials –> 8 lectures • 44min.
- Working with Corpora –> 8 lectures • 1hr 6min.
- POS Tagging & Chunking –> 6 lectures • 38min.
- Text Classification with NLTK –> 6 lectures • 36min.
- Language Modeling & N-grams –> 6 lectures • 1hr 2min.
- Named Entity Recognition (NER) & Syntax Trees –> 4 lectures • 22min.
- Information Extraction & Regex –> 4 lectures • 26min.
- WordNet and Semantic Analysis –> 7 lectures • 52min.
Requirements
This is one of the most hands-on and comprehensive courses ever built for Natural Language Processing (NLP) using the NLTK library in Python.
Whether you’re a student, developer, or researcher, this course will guide you step-by-step from the absolute basics of NLP to building your own mini projects like a Shakespeare-style text generator, resume parser, and synonym-based sentence rewriter — all using just Python and NLTK.
You won’t just learn the theory — you’ll apply it. Each section comes with real code walkthroughs, quizzes to test your understanding, and mini projects that you can proudly showcase in your portfolio.
What You’ll Learn:
- Tokenize and clean text data using NLTK’s powerful utilities
- Explore and analyze large corpora like Gutenberg, Brown, and Reuters
- Build your own autocomplete-like tool using n-gram language models
- Extract named entities like people, locations, and organizations from raw text
- Parse sentences using syntax trees and context-free grammar
- Use regular expressions for information extraction (emails, dates, names)
- Understand word meanings, synonyms, and relationships with WordNet
- Generate creative sentences and evaluate language models
- Write Python scripts that classify text, extract insights, and transform language
Projects You’ll Build:
- Author Style Analyzer (from corpus data)
- Resume Skill Extractor (from unstructured text)
- Shakespeare-Style Text Generator (using trigrams)
- Autocomplete Suggestion Engine (with n-grams)
- Synonym Sentence Swapper (using WordNet)
This course is purely focused on NLTK — it won’t cover modern neural network models or transformer libraries like spaCy, BERT, or HuggingFace. The goal is to master the foundations first by building real applications with simple, explainable tools.
By the end of this course, you’ll not only understand how NLP works, but also have a complete project portfolio built entirely with Python and NLTK — ready to impress employers, clients, or fellow learners.