What We Offer?

  • 8 Demos and 2 Industry standard project with self-paced solution explainer

  • Code files and Datasets

  • Unique story style learning

  • Self-paced Highly structured Learning references


  • Text Preprocessing

  • Bag of Words Feature Extraction

  • N-grams technique

  • NER

  • Noise Removal

  • TF-IDF

  • Feature Extraction Twitter Sentiment Analysis

  • Text Preprocessing Twitter Sentiment Analysis


Movie Review Classification

Your work is to study the data and create a sentiment classification model that can predict the number of positive and negative reviews based on sentiments by using different classification models. The analysis includes text preprocessing, classifying the reviews & evaluating the classifier.

Supporting Enterprises Around the Globe


Identify Topics from News Headlines

Your work is to study the data and use topic modeling techniques to find out the relevant topics in the headlines & compare different techniques. The analysis includes EDA, preprocessing & topic modelling with LSA and LDA techniques.

Target Audience

  • Anyone who is curious about data science and NLP

  • Anyone who wants a great hands-on experience in NLP


  • Basic Python programming knowledge is required

Natural Language Processing - Demos and Projects

Price INR 999/-

Course Curriculum

  • 1

    Course Introduction

  • 2

    Introduction to NLP

    • Lesson - Introduction

    • Introduction to NLP

    • Introduction to NLTK

    • Overview of NLTK modules

  • 3

    Text Preprocessing

    • Lesson - Introduction

    • Noise Removal - Stopwords, Punctuations

    • Hashtags

    • Regex

    • Lemmatization

    • Stemming

  • 4

    Demo-1 - Text Preprocessing

    • DEMO - Text Preprocessing

    • Demo Resources

  • 5

    Feature Engineering

    • Lesson - Introduction

    • Syntactic Parsing - Dependency Trees

    • Part of speech tagging

    • Word sense disambiguation

    • Entity Extraction - Named Entity Recognition (NER)

    • Topic Modeling

    • N-Grams as Features

    • Statistical Features - Term Frequency – Inverse Document Frequency (TF – IDF)

    • Count

    • Python Packages - Spacy

    • Python Packages - Gensim

    • Python Packages - Scikit-learn

    • Word Embedding - Word2Vec

    • Word Embedding - GloVe

    • Document Embedding - Doc2Vec

  • 6

    Demo-2 - Bag of Words Feature Extraction

    • DEMO - Bag of Words Feature Extraction

    • Demo Resources

  • 7

    Demo-3 - N-grams technique

    • DEMO - N-grams technique

    • Demo Resources

  • 8

    Demo-4 - NER

    • DEMO - NER

    • Demo Resources

  • 9

    Demo-5 - Noise Removal

    • DEMO - Noise Removal

    • Demo Resources

  • 10

    Demo-6 - TF-IDF

    • DEMO - TF-IDF

    • Demo Resources

  • 11

    NLP Applications

    • Lesson - Introduction

    • Text Classification - Sentiment Classification

    • Text Classification - Spam Detection

    • Text Similarity

    • Text Summarization

    • Machine Translation

  • 12

    Demo-7 - Feature Extraction Twitter Sentiment Analysis

    • DEMO - Feature Extraction Twitter Sentiment Analysis

    • Demo Resources

  • 13

    Demo-8 - Text Preprocessing Twitter Sentiment Analysis

    • DEMO - Text Preprocessing Twitter Sentiment Analysis

    • Demo Resources

  • 14


  • 15



  • After signing up for the course, after how much time would I get access to the Learning Content?

    As soon as you signed-up, you will have full access to the complete self-paced content.

  • How my doubts will be resolved?

    There is a discussion forum attached to each course in your LMS. You can post your questions and our expert(s) will answer the queries.

  • For how long do I have access to the course material?

    The training course content is available to you for lifetime.

Our Students Love Us.

Vishal Agnihotri

This is my first experience to online learning from learnkarts. The course was very engaging and the support provided was awesome. Overall, it is was a great learning experience and it helped me to get job in Python.

Yana Sri

The instructor of the training explained all the doubts patiently. It is very easy to learn from anywhere without any problem. Online forum support is excellent.

Ankit Vohra

The project was very good. Highly recommend this for anyone looking to learn Python.

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