Module 6

Natural Language Processing (NLP)
Ever wondered how Siri understands your questions or how Gmail autocompletes your sentences? Welcome to Module 6 of "Natural Language Processing (NLP)", where you'll discover the fascinating technology that enables computers to understand and interact with human language.
In this module, you'll master the core building blocks of NLP, from basic text preprocessing to advanced language generation. We'll explore practical techniques like tokenization, part-of-speech tagging, dependency parsing, and semantic analysis - the same technologies powering today's chatbots, translation services, and content analysis tools.
By the end of this module, you'll be equipped to build your own NLP applications. Whether you want to create a sentiment analyzer for social media, develop a language translation tool, or build an intelligent chatbot, you'll have the fundamental knowledge and practical skills to bring your ideas to life. Get ready to join the revolution in human-computer interaction!
Learning Objectives
Lesson 6.1: Introduction to NLP

Gain an understanding of Natural Language Processing (NLP), its applications across various domains such as chatbots, sentiment analysis, and language translation.

Lesson 6.2: Text Preprocessing

Learn essential preprocessing steps for cleaning and preparing text data, including tokenization, stemming, lemmatization, and handling stopwords.

Lesson 6.3: Sentiment Analysis

Explore techniques for analyzing and categorizing text, focusing on sentiment analysis to determine the sentiment (positive, negative, neutral) of text data.

Lesson 6.4: Hands-on Exercise

Engage in a practical exercise where you will build a sentiment analysis model using NLP techniques. Implement and evaluate a model that predicts sentiment from text data, applying preprocessing and classification algorithms.