Course Details

Natural Language Processing: Methods, Models and Applications

In today’s data-driven and AI-powered world, Natural Language Processing (NLP) plays a critical role in enabling machines to understand, interpret, and generate human language. NLP is at the core of in-demand technologies such as search engines, chatbots, sentiment analysis, machine translation, speech-to-text systems, and intelligent document processing. Therefore, to build industry-ready skills in NLP and Generative AI, this course is designed adopting a practical and hands-on approach. It is structured to connect core theory with real-world implementation, helping learners to confidently tackle practical AI and Data problems.

Course Objectives:
• Build a strong foundation in Python programming by understanding core language concepts, object-oriented programming, and leveraging libraries such as NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization.
• Preprocess, analyze, and extract insights from unstructured text data using Regular Expressions and industry-standard NLP libraries such as SpaCy and NLTK, enabling effective text cleaning and linguistic analysis.
• Understand and apply core machine learning concepts, including supervised and unsupervised learning, model evaluation metrics (accuracy, precision, recall, F1-score), and techniques to handle overfitting and underfitting.
• Design and implement end-to-end NLP solutions using classical machine learning models, text feature extraction techniques, word embeddings, and topic modeling for tasks such as text classification, sentiment analysis, and emotion detection.
• Develop industry-ready expertise in Generative AI by understanding Large Language Model architectures, transformer-based attention mechanisms, and applying tools such as GPT, BERT, RoBERTa, DistilBERT, XLNet, and Hugging Face to build, fine-tune, and deploy intelligent text-generation and question-answering systems.

Batch Details:
Class Timings: Tuesday, Thursday & Saturday (6:30 pm-7:30 pm);
Start Date: 20th Jan 2026 End Date: 30th May 2026
Duration: 54 Hours Mode: Online
Last Date to Register: 19th Jan 2026
Recorded lectures will be provided after each live session
This Link to Register:- https://rzp.io/rzp/NLPCourseRegistration

Course Highlights:
● Industry-Relevant High-In-Demand Skills in NLP Techniques.
● Hands-on based learning experience through practical projects.
● Globally accepted certification from iHUB Divyasampark IIT Roorkee
● Full-time access to recorded lectures/PPTs/PDFs/Study Materials.
● Session on Resume Preparation/Interview Preparation.

Contact Person: Dr. Subrat Kotoky
CTO, Ritvij Bharat Pvt. Ltd. (RBPL)
Ph.D. in Mechanical Engineering (IIT Guwahati)
rbpl.edu@gmail.com/subrat.kotoky@ritvij.co.in
9085317465/8473874389

Expert Profile: Mr. Shreyas Shukla
Professional Corporate Trainer & Microsoft Azure Certified Data Engineer
MTech-IIT Kharagpur & BE- The Aeronautical Society of India, New Delhi
4+ years of experience in leading online professional courses for different leading organizations

Has successfully conducted 25+ courses and trained 2000+ learners in the fields of Python Programming, Data Analytics, Machine Learning, Data Science, Database Management, Deep Learning, Computer Vision etc. till now.
Certifications:
1. DP-203: Microsoft Certified: Azure Data Engineer Associate
2. DP-900: Microsoft Certified: Azure Data Fundamentals
3. AZ-900: Microsoft Certified: Azure Fundamentals

Our Students Rate This Course

4.5

Trainer

RBPL

Program Fee

Rs 7500/-

Available Seats

100

Schedule

Class Timings: Tuesday, Thursday & Saturday (6:30 pm-7:30 pm);

Only Few Seats Left

All certificate images are for illustrative purposes only and may be subject to change at the discretion of the iHUB - IIT Roorkee.

What is included in this course?

Program Certificate form iHUB DivyaSampark, IIT Roorkee
Live & Self Paced learning for better engagement
No repetitive calls, only as per convenience
Opportunity to meet your mentors through Campus Immersion
25+ hand-on project with integrated labs

Apply Now To Secure a Seat!

Reviews

Testimonials

MODULE

1

· Basics of Python Language; Python objects with details of shell/numbers/variables etc.

· Comparison operators, Range, List, Comprehension, Functions, Lambda expressions

· Introduction to Object oriented programming using Python

· Introduction to NumPy, Random Functions, Reshape & Arithmetic Operations

· Introduction to Pandas-Data cleaning and preprocessing using Pandas

· Data visualization and Graphical plotting using Matplotlib and Pandas

MODULE

2

· Regular Expressions: Literals, Metacharacters, and escaping rules, Character classes, Ranges and negated sets.

· Predefined character classes. Grouping, capturing, non-capturing, and named groups

· Anchors, boundaries, and positional matching.

· Spacy: Tokenization, Part of Speech (POS) Tagging, Dependency Parsing.

· Lemmatization, Named Entity Recognition (NER), Vector and Cosine Similarity.

· NLTK: Stop Words, Stemming, WordNet, Collocations, N-grams.

MODULE

3

· Machine Learning Basics, introduction to supervised & unsupervised learning

· Logistic Regression, Sigmoid Function, Maximum Likelihood

· Confusion Matrix, interpreting parameters like F-1 score, Accuracy, Precision, Recall etc.

· Bias-variance trade off, Overfitting, Underfitting of Models

· NLP with Machine Learning Models like Naive-Bayes, Support Vector Machines

MODULE

4

· Text Feature Extraction, Bag of Words (BOW), TF-IDF (Term Frequency - Inverse Document Frequency)

· Document Term Matrix (DTM), word2vec, GloVe Vectors

· Topic Modelling, Input Embeddings

· Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA)

· NLP for Text Classification

· NLP for Sentiment Analysis

MODULE

5

· Generative AI: Introducing ChatGPT, Large Language Models (LLMs)

· Understanding LLMs, General Purpose Models, Pre-training and Fine Tuning

· Deep- Learning Basics, Transformer Architecture, Input Embeddings

· Multi-headed Attention, Feed-Forward Layer, Masked multi-head Attention

· Understanding GPT, Open AI API, Generating Text, Customizing GPT output

· and Fine Tuning

· Hugging Face, Transformer Pipeline, Pre-trained tokenizers, Special tokens

· Q&A models: BERT architecture, Tokenizer, Embeddings, Calculating response

· Creating QA bot, BERT, RoBERTa, DistilBERT, GPT vs BERT vs XLNET, XLNET Embeddings and Fine Tuning

NEWS & UPDATES

Career Transitions

55% Average Salary Hike

$1,27,000 Highest Salary

800+ Career Transitions

300+ Hiring Partners

Who Can Apply for the Course?

Basic knowledge of Python is useful but NOT Mandatory. We’ll start from scratch.
This course can be taken up by any undergraduate/postgraduate student of Basic & Applied Sciences, Engineering, and Computer Applications and also by Research Scholars/Faculties/Working Professionals who want to up-skill themselves
Participants need to have a laptop/PC (with a minimum of 4 GB RAM, 100 GB HDD, Intel i3processor) and proper internet/Wi-Fi connection.

About Program

At iHUB DivyaSampark, we are driven by the belief that young, innovative minds have immense potential to transform the world. Our core mission is to develop highly knowledgeable human resources with top-order, industry-relevant skills.
Whether you are looking for a career transition, a significant salary hike, or to master specialized knowledge, our programs provide the mentorship and practical exposure needed to achieve successful career outcomes and help you secure roles with our network of 300+ hiring partners