About Course

Master Natural Language Processing (NLP) and learn how to build intelligent AI systems that understand, analyze, generate, and interpret human language using industry-leading technologies such as Python, NLTK, spaCy, Hugging Face, TensorFlow, PyTorch, Large Language Models (LLMs), ChatGPT, and Generative AI. This industry-focused programme equips learners with practical skills in text analytics, sentiment analysis, chatbot development, speech processing, language translation, text classification, information extraction, and AI-powered conversational systems, preparing them for high-demand careers in Artificial Intelligence and Language Technologies. Through hands-on projects and real-world case studies, learners will develop production-ready NLP solutions that power business automation, customer experience, healthcare, finance, cybersecurity, legal technology, education, and enterprise AI applications.

Understand NLP fundamentals and industry applications
Use Python and text processing libraries for NLP
Apply tokenization, stemming, lemmatization, and POS tagging
Engineer text features: Bag of Words, TF-IDF, word embeddings
Build ML models for text classification, sentiment analysis, and NER
Apply deep learning for NLP: RNN, LSTM, Transformers, attention
Work with LLMs and Generative AI: GPT models, Hugging Face, RAG, prompt engineering
Build enterprise NLP applications: speech recognition, translation, conversational AI
Design, develop, and deploy an enterprise NLP capstone project

Course Content

Module 1: Introduction to Natural Language Processing
• Fundamentals of Natural Language Processing • NLP Applications Across Industries • AI Language Models • NLP Lifecycle

Module 2: Python Programming for NLP
• Python for NLP • Text Processing Libraries • Regular Expressions • Data Manipulation with Pandas

Module 3: Text Processing & Linguistics
• Text Cleaning • Tokenization • Stemming & Lemmatization • Stop Words Removal • Part-of-Speech Tagging

Module 4: Feature Engineering for NLP
• Bag of Words • TF-IDF • Word Embeddings • Vector Representation • Feature Extraction

Module 5: Machine Learning for NLP
• Text Classification • Sentiment Analysis • Spam Detection • Topic Modeling • Named Entity Recognition (NER)

Module 6: Deep Learning for NLP
• Recurrent Neural Networks (RNN) • Long Short-Term Memory (LSTM) • Transformer Models • Attention Mechanism • Sequence-to-Sequence Models

Module 7: Large Language Models & Generative AI
• GPT Models • Hugging Face Transformers • Prompt Engineering • Retrieval-Augmented Generation (RAG) • AI Chatbot Development

Module 8: Enterprise NLP Applications
• Speech Recognition • Machine Translation • Conversational AI • Document Intelligence • AI-Powered Customer Support

Module 9: NLP Model Deployment
• API Integration • Cloud AI Services • Model Optimization • AI Monitoring • Responsible AI

Module 10: Capstone Project
Design, develop, and deploy an enterprise Natural Language Processing solution such as an AI chatbot, intelligent document analyzer, sentiment analysis platform, or multilingual language application that solves a real-world business challenge.

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Learn Natural Language Processing (NLP) from Scratch

About Course

What Will You Learn?

Course Content

Module 1: Introduction to Natural Language Processing
• Fundamentals of Natural Language Processing • NLP Applications Across Industries • AI Language Models • NLP Lifecycle

Module 2: Python Programming for NLP
• Python for NLP • Text Processing Libraries • Regular Expressions • Data Manipulation with Pandas

Module 3: Text Processing & Linguistics
• Text Cleaning • Tokenization • Stemming & Lemmatization • Stop Words Removal • Part-of-Speech Tagging

Module 4: Feature Engineering for NLP
• Bag of Words • TF-IDF • Word Embeddings • Vector Representation • Feature Extraction

Module 5: Machine Learning for NLP
• Text Classification • Sentiment Analysis • Spam Detection • Topic Modeling • Named Entity Recognition (NER)

Module 6: Deep Learning for NLP
• Recurrent Neural Networks (RNN) • Long Short-Term Memory (LSTM) • Transformer Models • Attention Mechanism • Sequence-to-Sequence Models

Module 7: Large Language Models & Generative AI
• GPT Models • Hugging Face Transformers • Prompt Engineering • Retrieval-Augmented Generation (RAG) • AI Chatbot Development

Module 8: Enterprise NLP Applications
• Speech Recognition • Machine Translation • Conversational AI • Document Intelligence • AI-Powered Customer Support

Module 9: NLP Model Deployment
• API Integration • Cloud AI Services • Model Optimization • AI Monitoring • Responsible AI

Module 10: Capstone Project
Design, develop, and deploy an enterprise Natural Language Processing solution such as an AI chatbot, intelligent document analyzer, sentiment analysis platform, or multilingual language application that solves a real-world business challenge.

About Course

What Will You Learn?

Course Content

Module 1: Introduction to Natural Language Processing • Fundamentals of Natural Language Processing • NLP Applications Across Industries • AI Language Models • NLP Lifecycle

Module 2: Python Programming for NLP • Python for NLP • Text Processing Libraries • Regular Expressions • Data Manipulation with Pandas

Module 3: Text Processing & Linguistics • Text Cleaning • Tokenization • Stemming & Lemmatization • Stop Words Removal • Part-of-Speech Tagging

Module 4: Feature Engineering for NLP • Bag of Words • TF-IDF • Word Embeddings • Vector Representation • Feature Extraction

Module 5: Machine Learning for NLP • Text Classification • Sentiment Analysis • Spam Detection • Topic Modeling • Named Entity Recognition (NER)

Module 6: Deep Learning for NLP • Recurrent Neural Networks (RNN) • Long Short-Term Memory (LSTM) • Transformer Models • Attention Mechanism • Sequence-to-Sequence Models

Module 7: Large Language Models & Generative AI • GPT Models • Hugging Face Transformers • Prompt Engineering • Retrieval-Augmented Generation (RAG) • AI Chatbot Development

Module 8: Enterprise NLP Applications • Speech Recognition • Machine Translation • Conversational AI • Document Intelligence • AI-Powered Customer Support

Module 9: NLP Model Deployment • API Integration • Cloud AI Services • Model Optimization • AI Monitoring • Responsible AI

Module 10: Capstone Project Design, develop, and deploy an enterprise Natural Language Processing solution such as an AI chatbot, intelligent document analyzer, sentiment analysis platform, or multilingual language application that solves a real-world business challenge.

Student Ratings & Reviews

Module 1: Introduction to Natural Language Processing
• Fundamentals of Natural Language Processing • NLP Applications Across Industries • AI Language Models • NLP Lifecycle

Module 2: Python Programming for NLP
• Python for NLP • Text Processing Libraries • Regular Expressions • Data Manipulation with Pandas

Module 3: Text Processing & Linguistics
• Text Cleaning • Tokenization • Stemming & Lemmatization • Stop Words Removal • Part-of-Speech Tagging

Module 4: Feature Engineering for NLP
• Bag of Words • TF-IDF • Word Embeddings • Vector Representation • Feature Extraction

Module 5: Machine Learning for NLP
• Text Classification • Sentiment Analysis • Spam Detection • Topic Modeling • Named Entity Recognition (NER)

Module 6: Deep Learning for NLP
• Recurrent Neural Networks (RNN) • Long Short-Term Memory (LSTM) • Transformer Models • Attention Mechanism • Sequence-to-Sequence Models

Module 7: Large Language Models & Generative AI
• GPT Models • Hugging Face Transformers • Prompt Engineering • Retrieval-Augmented Generation (RAG) • AI Chatbot Development

Module 8: Enterprise NLP Applications
• Speech Recognition • Machine Translation • Conversational AI • Document Intelligence • AI-Powered Customer Support

Module 9: NLP Model Deployment
• API Integration • Cloud AI Services • Model Optimization • AI Monitoring • Responsible AI

Module 10: Capstone Project
Design, develop, and deploy an enterprise Natural Language Processing solution such as an AI chatbot, intelligent document analyzer, sentiment analysis platform, or multilingual language application that solves a real-world business challenge.