Natural Language Processing (NLP) Course in chennai

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Natural Language Processing (NLP) Course in Chennai

Master the science of enabling computers to understand and process human language with Edubrights’ Natural Language Processing (NLP) training in Chennai. This course is designed for students, freshers, AI enthusiasts, data scientists, machine learning engineers, software developers, and working professionals who want to build intelligent language-based applications.

Gain hands-on experience with text processing, language modeling, sentiment analysis, text classification, named entity recognition, chatbots, NLP pipelines, and real-world AI projects through practical industry use cases.

Key Highlights:

✅ Real-Time NLP Projects & Industry-Based Use Cases

✅ Live Instructor-Led Training by AI & NLP Industry Experts

✅ Hands-On Practice with Python & NLP Libraries

✅ Text Processing, Tokenization & Language Preprocessing Techniques

✅ Sentiment Analysis & Opinion Mining Applications

✅ Text Classification & Document Categorization Workflows

✅ Named Entity Recognition (NER) & Information Extraction

✅ Language Modeling & Text Generation Concepts

✅ Chatbot Development & Conversational AI Applications

✅ NLP Pipeline Development for Real-World Business Scenarios

✅ Integration with Machine Learning & Deep Learning Models

✅ Practical Exposure to Transformer Models & Modern NLP Techniques

✅ Resume Building, Portfolio Development & Mock Interview Preparation

✅ Career Guidance, Placement Assistance & Certification Support

✅ Flexible Online, Classroom & Weekend Training Options

✅ Corporate Training for AI, NLP & Data Science Teams

Build practical NLP expertise, create intelligent language-driven applications, and become industry-ready for careers in Artificial Intelligence, Machine Learning, Data Science, and Language Technologies.

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₹30000

₹38000

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Case Studies and Projects

Hours of Training

20+

Placement Assurance

100%

Expert Support

Yes

Support & Access

Lifetime

Certification

Yes

Skill Level

All

Language

All

Course Objectives

1. Why should I learn Natural Language Processing (NLP)?

Natural Language Processing (NLP) enables computers to understand, analyze, and generate human language. Learning NLP opens career opportunities in Artificial Intelligence, Machine Learning, chatbots, sentiment analysis, and intelligent automation.

2. How will this NLP course improve my AI and data science skills?

This course teaches you how to process text data, build NLP models, perform language analysis, and develop intelligent applications using industry-standard Python libraries and machine learning techniques.

3. Is this NLP training suitable for beginners?

Yes. The course begins with Python and text processing fundamentals before progressing to advanced NLP concepts like language modeling, transformers, sentiment analysis, and conversational AI.

4. What practical experience will I gain during the training?

You will work on real-world NLP projects involving text classification, chatbot development, document analysis, language translation, and predictive text applications using practical datasets.

5. How does this NLP course help me build a career in Artificial Intelligence?

The training focuses on hands-on implementation, model development, industry projects, and deployment techniques that prepare you for AI, Machine Learning, and Data Science roles across multiple industries.

Popular Techniques Covered in This Course

Python for Natural Language Processing

Text Preprocessing & Cleaning

Tokenization & Text Normalization

Natural Language Understanding (NLU)

Sentiment Analysis

Named Entity Recognition (NER)

Text Classification Models

Machine Learning for NLP

Transformer Models & BERT Basics

NLP Project Deployment

Get Hands-on Knowledge about Real-Time Projects

Project 1

1. AI-Powered Customer Support Chatbot

Develop an intelligent chatbot capable of answering customer queries, understanding user intent, managing conversations, and integrating with business knowledge bases using NLP techniques.

Project 2

2. Social Media Sentiment Analysis Platform

Build a system that collects social media posts, analyzes customer opinions, identifies positive and negative sentiment, and generates actionable business insights through interactive dashboards.

Project 3

3. Resume Screening & Candidate Recommendation System

Create an NLP-based recruitment solution that extracts candidate information, matches resumes with job descriptions, ranks applicants, and simplifies the hiring process.

Project 4

4. News Article Classification & Recommendation Engine

Design an application that automatically categorizes news articles into multiple topics and recommends relevant content based on user interests and reading behavior.

Project 5

5. Intelligent Document Search & Information Extraction System

Develop an enterprise solution that processes large document collections, extracts important information, identifies entities, and enables fast semantic search across business documents.

Key Features

Edubrights offers NLP Training in virtual mode with expert trainers. Here are the key features,

40 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Curriculum

Module 1: Introduction to NLP

What is NLP and key application areas
NLP pipeline overview: text input to structured output
Challenges in NLP: ambiguity, context, and language diversity
NLP tools and libraries: NLTK, spaCy, and Hugging Face overview

Module 2: Text Preprocessing and Representation

Tokenisation: word, sentence, and subword tokenisation
Stopword removal, stemming, and lemmatisation
Bag-of-words, TF-IDF, and n-gram representations
Text normalisation and cleaning best practices

Module 3: Classical NLP Techniques

Part-of-speech tagging and dependency parsing
Named entity recognition with spaCy
Coreference resolution overview
Rule-based NLP with regex and pattern matching

Module 4: Text Classification and Sentiment Analysis

Supervised text classification with Naive Bayes and SVM
Sentiment analysis: lexicon-based and ML approaches
Multi-class and multi-label text classification
Evaluation metrics: accuracy, precision, recall, and F1

Module 5: Word Embeddings and Semantic Representations

Word2Vec: CBOW and Skip-gram models
GloVe and FastText word embeddings
Sentence embeddings with Sentence-BERT
Visualising and analysing word embedding spaces

Module 6: Sequence Models and Attention

RNNs, LSTMs, and GRUs for sequence modelling
Sequence-to-sequence models for translation and summarisation
Attention mechanism explained intuitively
Introduction to transformer architecture for NLP

Module 7: Transformer-Based NLP with Hugging Face

BERT for text classification and NER fine-tuning
GPT-2 for text generation tasks
T5 for summarisation, translation, and Q&A
Practical fine-tuning and evaluation with Hugging Face Trainer

Module 8: Hands-on Projects and Assessment

Building a sentiment analysis system for product reviews
NER and information extraction pipeline project
Text summarisation application with transformer models
Final assessment and course certification

Receive Training From Our Skilled and Effective Trainers

Experience in the Industry Learn from NLP researchers and engineers who have built text classification, sentiment analysis, information extraction, and conversational AI systems for enterprise applications.

Backgrounds at the Top Our NLP trainers have worked on language AI projects at leading technology companies, research institutions, and AI-focused consultancies across India and globally.

Clear & Effective Teaching NLP fundamentals including tokenisation, POS tagging, NER, text classification, and language modelling are taught clearly from traditional methods to modern transformer-based approaches.

Hands-On Learning Focus Students build practical NLP projects including sentiment analysis, text summarisation, and named entity recognition using NLTK, spaCy, and Hugging Face Transformers.

Up-to-Date Knowledge Trainers continuously update the curriculum with the latest NLP advances including large language models, multilingual NLP, and domain-specific fine-tuning techniques.

Natural Language Processing (NLP) Professional Certification

Successfully completing the Natural Language Processing (NLP) training certifies your ability to develop intelligent language-based applications using Python, machine learning, and modern NLP frameworks.

Course FAQs

1. What is Natural Language Processing (NLP)?

Natural Language Processing is a branch of Artificial Intelligence that enables computers to understand, interpret, analyze, and generate human language.

2. Who can enroll in this NLP course?

Students, graduates, software developers, AI enthusiasts, data analysts, machine learning engineers, and working professionals interested in Artificial Intelligence can join.

3. Are there any prerequisites for learning NLP?

Basic programming knowledge is helpful, but the course starts from the fundamentals, making it suitable for beginners.

4. Which programming language is used in this course?

Python is primarily used because of its extensive NLP libraries and strong industry adoption.

5. Will I work with real datasets?

Yes. The training includes practical exercises using real-world datasets for text analysis, prediction, and language processing.

6. Which NLP libraries will I learn?

You'll gain hands-on experience with libraries such as NLTK, spaCy, Hugging Face Transformers, TextBlob, and Scikit-learn.

7. Does the course include machine learning concepts?

Yes. You'll learn how machine learning algorithms are applied to solve NLP problems such as classification, prediction, and language understanding.

8. Will I learn chatbot development?

Yes. The course covers the concepts required to build intelligent conversational applications and AI-powered chatbots.

9. Are transformer models included in the curriculum?

Yes. You'll receive an introduction to modern transformer architectures, including BERT and other pre-trained language models.

10. Will I learn sentiment analysis?

Yes. The course teaches sentiment analysis techniques for customer reviews, social media content, and business intelligence applications.

11. Is this course suitable for Data Science careers?

Absolutely. NLP is one of the most in-demand skills in Artificial Intelligence and Data Science industries.

12. Will practical projects be included?

Yes. Every learner completes industry-oriented NLP projects to strengthen practical knowledge and improve employability.

13. Is placement assistance available?

Yes. Resume building, interview preparation, mock interviews, and placement support are included as part of the training.

14. Can I attend this NLP course online?

Yes. Both classroom and instructor-led online training options are available with practical lab sessions.

15. What job opportunities are available after completing NLP training?

You can apply for roles such as NLP Engineer, AI Developer, Machine Learning Engineer, Data Scientist, AI Research Associate, and Conversational AI Developer.