Natural Language Processing

Introduction

This Natural Language Processing (NLP) course is designed to equip learners with the practical and theoretical foundations of computational linguistics. Focusing on the analysis, processing, and generation of human language data, the course introduces essential NLP tasks such as text preprocessing, tokenization, POS tagging, named entity recognition, sentiment analysis, and language modeling. Learners will gain hands-on experience using popular NLP libraries such as NLTK, spaCy, Hugging Face Transformers, and Scikit-learn, enabling them to build real-world language-aware applications.

Objectives

By the end of this course, participants will be able to:

Understand core NLP concepts and linguistic structures in text data
Perform text preprocessing, cleaning, and transformation tasks
Build NLP models for classification, tagging, and text generation
Use pre-trained language models (e.g., BERT, GPT) for downstream tasks
Apply sentiment analysis, topic modeling, and entity recognition to real datasets
Deploy NLP models in applications such as chatbots, search engines, or text summarizers

Career Path

NLP Engineer
Machine Learning Engineer (NLP track)
AI Research Assistant (Language Focused)
Chatbot Developer / Voice Assistant Engineer
Data Scientist (Text Analytics)
Search Engine Optimization Analyst (Text Mining)
Linguistic Data Analyst / Annotator

Fee Structure Natural Language Processing

Natural Language Processing
Duration	12 Weeks
Total Semester	1
Total Package	20,000
At Admission Time	20,000
Additional Charges at the time of Admission	0
Examination Fee	0
Total Amount (At Admission)	20,000
Installment	0 * 2

Additional Charges at the time of Admission
Web Portal fee per year for Learning Management Syste	0
Library Security Fee (Refundable)	0
Student Card	0
Library & Magazine Fund	0
Total Additional Charges	0