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data Intermediate 21 lessons

Natural Language Processing

Teach computers to read and understand text. Master text preprocessing, sentiment analysis, and classification using NLTK and Spacy libraries.

Natural Language Processing (NLP) is the foundation of modern AI interaction. This course covers the essential techniques required to process and analyze human language. You will learn to clean raw text (tokenization, stemming, lemmatization), perform part-of-speech tagging, and build models for sentiment analysis and text classification. Using libraries like NLTK and Spacy, you will transform unstructured text into structured data that machines can understand, paving the way for advanced LLM work.

✅ 100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
NLP Lab
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Complete Course Syllabus

  • 1
    Text Cleaning
    Removing noise, stop words, and normalizing text data.
  • 2
    Tokenization
    Splitting text into words and sentences for analysis.
  • 3
    Feature Extraction
    Converting text to numbers using Bag of Words and TF-IDF.
  • 4
    Sentiment Analysis
    Building models to detect positive or negative tone.
  • 5
    Named Entity Recognition
    Identifying and labeling real-world objects in text.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$115k - $150k

Career Paths

NLP Engineer $120k-$160k
Data Scientist $115k-$150k
AI Product Developer $110k-$145k

What You Will Learn

Preprocess raw text data using tokenization and lemmatization techniques
Build sentiment analysis models to gauge public opinion
Classify text documents into categories using machine learning
Extract named entities like people and places from text
Implement TF-IDF vectorization to measure word importance

Skills You Will Gain

Text Preprocessing Sentiment Analysis NLTK Spacy Regular Expressions

Who Is This For

Data Scientists
Linguists
AI Developers

Prerequisites

Python Proficiency
Basic ML Concepts

Natural Language Processing FAQs

LLMs included?

This covers the foundations required to understand LLMs.

Language support?

We focus on English, but concepts apply globally.

Is coding heavy?

Yes, extensive text manipulation with Python scripts.

Real applications?

Spam filters, chatbots, and review analysis tools.

Need more info?
All Reork courses are 100% free, self-paced, and fully accessible on mobile devices. No prior experience is required. Read our full Platform FAQ.

Tech Stack & Tools

Python
NLTK
Spacy
Scikit-Learn
Regex

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Your Learning Path

Master This Topic, Step by Step

Go from your first step to master level. Three simple steps, all about Natural Language Processing.

Currently studying: Natural Language Processing
Step 1 · Easy Start

Natural Language Processing Basics

New to Natural Language Processing? Start here. Learn the basics in small, easy steps.

5 min Free to explore
Natural Language Processing for Beginners
Begin here — no experience needed
Step 2 · Keep Going

Advanced Natural Language Processing

Most people stop at the basics. Keep going — this step takes you higher.

5 min Free to explore
Advanced Natural Language Processing Course
Go deeper — the next 5 minutes are worth it
Step 3 · Master With AI

Master Natural Language Processing with AI

This is the shortcut: Ollama + Local LLMs helps you run powerful AI models on your own machine — and master Natural Language Processing faster.

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Local AI Models
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Start with Step 1. Each step builds on the one before it.
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