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Natural Language Processing : From Text to Intelligence
Rating: 5.0 out of 5(2 ratings)
18 students

Natural Language Processing : From Text to Intelligence

Master NLP, Text Preprocessing, Sentiment Analysis, TF-IDF, POS, NER & build a real-world customer analytics project
Created byRajneet Kaur
Last updated 8/2026
English

What you'll learn

  • Build a real-world NLP customer analytics project using Python
  • Understand the complete NLP pipeline from raw text to business insights
  • Perform text preprocessing using tokenization, stemming, lemmatization, and stopword removal
  • Apply Bag of Words, TF-IDF, POS Tagging, and Named Entity Recognition on text data

Course content

5 sections • 15 lectures • 58m total length
  • About the course0:49

    Course overview & learning outcomes

  • Her movie - Samantha's capabilities1:49

    Explore real-world NLP capabilities through the movie Her

  • Her movie NLP breakdown3:37

    Map Samantha's abilities to core NLP concepts and techniques

Requirements

  • Basic Python knowledge is recommended but not mandatory
  • No prior NLP or AI experience required

Description

Every day, businesses generate massive amounts of text—from customer reviews and emails to support tickets, surveys, and social media posts. Natural Language Processing (NLP) enables us to transform this unstructured text into meaningful insights that drive better decisions.

In this beginner-friendly course, you'll learn the core concepts of Natural Language Processing using practical examples and hands-on Python implementation. Rather than diving into complex mathematics, the course focuses on building strong intuition and applying NLP techniques to real-world business problems.

We'll start by understanding what NLP is, why it has become one of the most important areas of Artificial Intelligence, and where it is used in everyday applications. Using relatable examples and popular movies, you'll discover how computers interpret and understand human language.

Next, you'll master the complete NLP pipeline, including text preprocessing techniques such as tokenization, stopword removal, stemming, and lemmatization. You'll then learn how text is converted into numerical features using Bag of Words and TF-IDF.

The course also covers two of the most widely used NLP techniques—Part-of-Speech (POS) Tagging and Named Entity Recognition (NER)—to understand sentence structure and identify important entities from text.

Finally, you'll apply everything you've learned by building a customer analytics case study using Python, demonstrating how NLP can uncover business insights from customer reviews.

What you'll learn

  • Understand the complete NLP workflow

  • Clean and preprocess text data

  • Apply stemming, lemmatization, POS tagging, and NER

  • Convert text into machine learning features using Bag of Words and TF-IDF

  • Build an end-to-end NLP project using Python

  • Understand practical NLP applications across industries

Whether you're a student, aspiring data scientist, AI enthusiast, analyst, or business professional, this course will give you a strong foundation in Natural Language Processing and prepare you to explore advanced NLP and Generative AI topics with confidence.

Who this course is for:

  • Data analysts, AI ML enthusiasts and aspiring data scientists
  • Entrepreneurs and business professionals who want to extract insights from text data