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Free Natural Language Processing Course
Introduction to Natural Language Processing
Enhance your AI expertise by enrolling in the free NLP Course, covering essential topics such as Data Pre-processing, NLP Modeling Techniques. Acquire in-demand skills through this comprehensive natural language processing course.
Instructor:
Ms. Sampriti ChatterjeeLevel
Learning hours
Learners
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Skills you will learn
About this course
This free NLP course starts by introducing you to NLP and Python. You will learn about data pre-processing and learn to work with different types of documents using Python. You will understand tokenization, its needs, and its implementation through this NLP course. You will go through a hands-on session online and word tokenization implementation using Python programming. Understand stemming, lemmatization, and stopwords better with the hands-on sessions on their implementation using Python.
You will learn about the bag of words and TF-IDF models and comprehend word embedding. In this free Introduction to NLP course, you will then learn about Machine Learning, logistic regression, and sentiment analysis. You will go through a thorough demo on sentiment analysis and learn about TextBlob. Learn TextBlob, and its functionalities and go through TextBlob sentiment analysis. Lastly, you will go through U-Net, semantic segmentation, and their demo. Enroll in this free Introduction to Natural Language Processing course and complete the quiz at the end to earn a certificate of course completion.
Check out Great Learning’s Best Artificial Intelligence Courses and dwell more into emerging technologies in the industry. Enroll in the course you are interested in and achieve a certificate of course completion.
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Course Outline
In this module, you will get introduced to NLP and its various popular examples. You will go through the roadmap to learn NLP and understand the implementation of the technique through Python.
In this module, you will learn Python and comprehend why its chosen for the implementation of NLP. You will learn about the Python programming language’s benefits and its important libraries.
This module helps you comprehend what data is and how to work with different types of documents using Python programming language. You will then understand data pre-processing through the Python hands-on session and understand the types of data pre-processing.
In this module of the NLP course, you will learn tokenization and understand why you need tokenization. You will then go through a demo on implementing tokenization using Python. You will implement line and word tokenization using Python programming language.
In this module, you will learn stemming and understand the need for stemming. You will also go through a hands-on session on implementing stemming using Python programming language.
In this module, you will learn about lemmatization in NLP and go through the differences between stemming and lemmatization. You will then go through a hands-on session on lemmatization using Python programming.
In this module, you will learn what stopwords are and go through a hands-on session on removing stopwords using Python.
In this module of the NLP course, you will learn about the bag of words and TF-IDF models and understand why you need TF-IDF. You will also comprehend what word embedding is.
This module starts by discussing Machine Learning, the life cycle of Machine Learning, and the types of Machine Learning. You will also learn logistic regression in detail.
This module will help you understand sentiment analysis in detail to comprehend Natural Language Processing better.
This module contains a hands-on session on the sentiment analysis project using Python programming language.
This module briefly describes TextBlob and its aid in Natural Language Processing(NLP).
This module gives you an overview of NLP you have learned from the previous modules. You will get a brief on NLP, data pre-processing, stemming, lemmatization, and text vectorization.
This module introduces you to TextBlob in detail and will also guide you in installing it.
This module contains a hands-on session on TextBlob and functionalities of TextBlob, like language detection, POS tagging, tokenization, pluralization of words using TextBlog, and more.
This module contains a hands-on session on TextBlob sentiment analysis using the IMDB dataset. You will also go through polarity, subjectivity, and data preprocessing.
This module introduces you to U-Net, a convolutional neural network for image segmentation. You will thoroughly understand it with the help of the given examples.
In this module, you will learn semantic segmentation with the help of an image example. You will also comprehend instance segmentation, U-net, and standard convolutions.
This module contains a detailed hands-on demo on semantic segmentation using Python programming language.
Earn a certificate of completion
Get free course content
Learn at your own pace
Master in-demand skills & tools
Test your skills with quizzes
What our learners enjoyed the most
Skill & tools
65% of learners found all the desired skills & tools
Our course instructor

Ms. Sampriti Chatterjee
Artificial Intelligence Expert


Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What prerequisites are required to learn this Introduction to Natural Language Processing course?
There are no prerequisites required to get started with this free NLP course. It is a beginner’s course; hence novice learners can start NLP from scratch.
How long does it take to complete this free NLP course?
This free Introduction to Natural Language Processing course contains 4.5 hours of self-paced videos that learners can take up according to their convenience.
What are my next learning options after this Introduction to NLP course?
You can enroll in Great Learning’s Best PG Artificial Intelligence Course online by the University of Texas at Austin’s McCombs School of Business.
Will I get a certificate after completing this Introduction to Natural Langauge Processing course?
Yes, you will be rewarded with a free NLP course completion certificate after completing all the modules and the quiz at the end of this free Introduction to Natural Language Processing course.
How much does this NLP course cost?
This Introduction to NLP course is offered for free by Great Learning Academy.
Is there a limit on how many times I can take this Introduction to Natural Language Processing course?
No, there are no such limits on the number of times you can attain this Introduction to NLP course.
Can I sign up for multiple courses from Great Learning Academy at the same time?
Yes, you can sign up for more than one free course offered by Great Learning Academy that fastens your effective career development.
Why choose Great Learning for this Introduction to NLP course?
Great Learning Academy is an initiative taken by the leading e-learning platform, Great Learning. Great Learning Academy provides you with industry-relevant courses for free, and Introduction to Natural Langauge Processing is one of the free courses that empowers you with in-demand skills.
What are the steps to enroll in this course?
- Search for the free “Introduction to Natural Language Processing” course in the search bar present at the top corner of Great Learning Academy.
- Register for the course through the Enroll Now button and start learning.
Will I have lifetime access to this free online course?
Yes. You will have lifetime access to this free online Introduction to Natural Language Processing course.
Is it worth learning NLP?
Natural Language Processing comes under computer science and artificial intelligence that focuses on the interactions between computers and human languages, particularly how to program computers to process and analyze large amounts of natural language data. As a result, learning about NLP is worthwhile.
What is NLP used for?
Natural Language Processing is used for various tasks, including text classification, topic modeling, sentiment analysis, and text generation. Various tasks involving the analysis and processing of text data include the usage of Natural Language Processing (NLP). Speech recognition, named entity recognition, and language detection are a few of these tasks that can be performed. Due to its ability to improve understanding and communication can also be employed in commercial settings, such as sales and marketing.
Why is NLP so popular?
Due to its focus on how people and computers communicate, the field of Artificial Intelligence known as Natural Language Processing is very well-liked. Natural Language Processing is a particularly efficient method for processing and analyzing massive amounts of data, which is one of the key reasons it is so popular. This is particularly true for text-based data, as it can be quite challenging to examine this data using conventional techniques. This procedure can be automated with the help of Natural Language Processing, making it much simpler to comprehend and evaluate the data.
What jobs demand that you learn NLP?
Jobs that demand you learn Natural Language Processing include:
- Artificial Intelligence Researcher
- Computational Linguist
- Data Analyst
- Data Miner
- Data Scientist
- Information Retrieval Specialist
- Machine Learning Engineer
- NLP Developer
- NLP Engineer
- Research Scientist
What knowledge and skills will I gain upon completing this NLP course?
By the end of this Introduction to NLP course, you will learn about Natural Language Processing, tokenization, stemming, lemmatization, removing stopwords, various modeling techniques in NLP, sentiment analysis, TextBlob, U-Net, and Semantic segmentation.
Who is eligible to take this NLP course?
Any beginner or novice learner who wants to get acquainted with Natural Langauge Processing can enroll in this free NLP course.
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