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Pro & University Programs

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McCombs School of Business at The University of Texas at Austin

7 months  • Online

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MIT IDSS

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Free NLP Courses

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Introduction to Natural Language Processing
star   4.52 43.1K+ learners
4.5 hrs
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Introduction to Text Mining
star   4.67 1.2K+ learners
1 hr
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Textblob
star   4.58 1.8K+ learners
1.5 hrs
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Introduction to Neural Networks and Deep Learning
star   4.57 67.8K+ learners
2.5 hrs
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Machine Translation
star   4.53 4.5K+ learners
1.5 hrs
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Semantic Segmentation Tutorial
star   4.59 1.9K+ learners
1.5 hrs
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How to Build your own Chatbot using Python?
star   4.51 38K+ learners
1.5 hrs
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Sentiment Analysis using Python
star   4.48 19.8K+ learners
1.5 hrs
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Natural Language Processing Projects
star   4.62 7.9K+ learners
2.5 hrs
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Introduction to Natural Language Processing
star   4.52 43.1K+ learners 4.5 hrs
img icon FREE
Introduction to Text Mining
star   4.67 1.2K+ learners 1 hr
img icon FREE
Textblob
star   4.58 1.8K+ learners 1.5 hrs
img icon FREE
Introduction to Neural Networks and Deep Learning
star   4.57 67.8K+ learners 2.5 hrs
img icon FREE
Machine Translation
star   4.53 4.5K+ learners 1.5 hrs
img icon FREE
Semantic Segmentation Tutorial
star   4.59 1.9K+ learners 1.5 hrs
img icon FREE
How to Build your own Chatbot using Python?
star   4.51 38K+ learners 1.5 hrs
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Sentiment Analysis using Python
star   4.48 19.8K+ learners 1.5 hrs
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Natural Language Processing Projects
star   4.62 7.9K+ learners 2.5 hrs

Get started with these courses

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LLM Essentials
108 learners
1 hr
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Introduction to Text Mining
star   4.67 1.2K+ learners
1 hr
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Machine Translation
star   4.53 4.5K+ learners
1.5 hrs
img icon FREE
Textblob
star   4.58 1.8K+ learners
1.5 hrs
img icon FREE
Natural Language Processing Projects
star   4.62 7.9K+ learners
2.5 hrs
img icon FREE
Semantic Segmentation Tutorial
star   4.59 1.9K+ learners
1.5 hrs
img icon FREE
NLP Customer Experience
star   4.52 4.1K+ learners
1 hr
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NLP Interview Questions and Answers
star   4.5 2.1K+ learners
1.5 hrs
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Introduction to Neural Networks and Deep Learning
star   4.57 67.8K+ learners
2.5 hrs
img icon FREE
Introduction to Natural Language Processing
star   4.52 43.1K+ learners
4.5 hrs
img icon FREE
How to Build your own Chatbot using Python?
star   4.51 38K+ learners
1.5 hrs
img icon FREE
Sentiment Analysis using Python
star   4.48 19.8K+ learners
1.5 hrs

New

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LLM Essentials
108 learners
1 hr
img icon FREE
Introduction to Text Mining
star   4.67 1.2K+ learners
1 hr
img icon FREE
Machine Translation
star   4.53 4.5K+ learners
1.5 hrs
img icon FREE
Textblob
star   4.58 1.8K+ learners
1.5 hrs

Trending

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Natural Language Processing Projects
star   4.62 7.9K+ learners
2.5 hrs
img icon FREE
Semantic Segmentation Tutorial
star   4.59 1.9K+ learners
1.5 hrs
img icon FREE
NLP Customer Experience
star   4.52 4.1K+ learners
1 hr
img icon FREE
NLP Interview Questions and Answers
star   4.5 2.1K+ learners
1.5 hrs

Popular

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Introduction to Neural Networks and Deep Learning
star   4.57 67.8K+ learners
2.5 hrs
img icon FREE
Introduction to Natural Language Processing
star   4.52 43.1K+ learners
4.5 hrs
img icon FREE
How to Build your own Chatbot using Python?
star   4.51 38K+ learners
1.5 hrs
img icon FREE
Sentiment Analysis using Python
star   4.48 19.8K+ learners
1.5 hrs

Learner reviews of the Free NLP Courses

Our learners share their experiences of our courses

4.53
70%
22%
6%
1%
2%
Reviewer Profile

4.0

“The Learning Experience Was Engaging and Well-Structured, Maintaining Interest Throughout. The Material Was Presented Clearly, Making Complex Concepts Easy to Grasp.”
The learning experience was engaging and effectively maintained my interest. The content was presented clearly and was easy to understand, aligning well with the course objectives. The knowledge and skills acquired are applicable to real-world scenarios. The instructor demonstrated strong effectiveness in delivering the material and fostering discussions. The provided resources were valuable and supported my learning. Overall, the experience was positive, providing useful insights and areas for potential improvement.

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Reviewer Profile

4.0

“It Was Fascinating and Compelling.”
The course was great, from the breakdown to in-depth illustrations using use cases.

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Reviewer Profile

4.0

“Engaging and Informative Course!”
I found the course content to be very well-structured and easy to follow. The instructor's explanations were clear and concise, making complex topics accessible. I particularly appreciated the real-world examples and practical exercises that helped solidify my understanding of the material. Overall, this course was a valuable learning experience that exceeded my expectations.

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Reviewer Profile

5.0

“Very Good Course for NLP, Enjoyed Taking Up the Course.”
The course was very helpful for me as I am a beginner. Everything is explained in detail, and the explanation was very good.

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Reviewer Profile

5.0

“It Has Been an Incredibly Insightful Experience”
I particularly appreciated how the course introduced both the theoretical concepts and practical applications, allowing me to gain hands-on experience with real-world datasets. However, it can be improved if you provide datasets used in the hands-on video, which will make it easier while learning.

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Reviewer Profile

5.0

“Comprehensive and Practical NLP Course”
The instructors explain complex topics clearly, with engaging examples and case studies. However, more focus on real-world deployment could improve the course further. Overall, it's a great course for anyone looking to dive into NLP, whether for academic purposes or to gain practical skills for industry applications.

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Reviewer Profile

4.0

“I Got to Know More About Natural Language Processing.”
The course offers a comprehensive overview of NLP concepts, including text processing, language models, and sentiment analysis. The structured curriculum combines video lectures with hands-on assignments, facilitating practical learning. Instructors are knowledgeable, providing valuable insights into the field. However, some advanced topics could benefit from deeper exploration, and prior programming knowledge (especially in Python) is recommended for beginners. Overall, it's a well-received course for those looking to build a solid foundation in NLP.

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Reviewer Profile

5.0

“A Truly Upskilling Course Which Helped in Enlightening My Field of Study”
Right from the start, the courses, the curriculum, the faculties, the methods, and most importantly, the examples used were all on point and easy to capture. This course will surely help me in my academics as well as future endeavors.

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Reviewer Profile

5.0

“Good and Easy to Learn”
Helpful to add a new skill to a resume. Good instructor.

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Reviewer Profile

5.0

“Easy and Fast Tutorial for NLP. Very Helpful.”
The course is very helpful. It is short and precise, and there are plenty of examples and hands-on experience.

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Take Free NLP Courses and Get Certificates

NLP is Natural Language Processing. It is dependent on Computer Science, Artificial Intelligence, and Human Language. NLP is the technology that is used by machines for understanding, analyzing, manipulating, and interpreting human languages. Developers highly use it in completing tasks like speech recognition, translation, automatic summarization, Named Entity Recognition (NER), relationship extraction, and topic segmentation.

 

The two main components of NLP are:

 

  • Natural Language Understanding (NLU)

NLU extracts the metadata from contents like keywords, concepts, entities, emotions, relations, and semantic roles, through which it helps the machines to understand and analyze the human language.

 

NLU is mainly used in business applications for understanding customer needs both in written and spoken language. NLP is used in mapping the input to the proper representation. It is also used in analyzing the various aspects of language. 

 

  • Natural Language Generation (NLG)

NLG helps in converting the computerized data into natural language representation. It acts as a translator. It mainly covers text planning, sentence planning, and text realization.

 

NLU is more complicated than NLG. Producing non-linguistic outputs from natural language inputs is done by NLU. In contrast, NLG obtains constructing natural language outputs from non-linguistic inputs.

 

Applications of NLP are:

 

  • Question Answering: NLP helps in developing systems that can automatically answer your questions when asked in a natural language. For example, Alexa.
  • Spam Detection: You can train your model with the help of NLP regarding the separation of wanted and unwanted emails. This allows spam detection and getting rid of unwanted emails from user inboxes.
  • Sentiment Analysis: It is used on the web to detect and analyze the user’s behavior, attitude, and emotional state. A combination of NLP and statistics is used to develop this application that assigns values to the text in order to identify the mood of the context. It is also known as Opinion Mining.
  • Machine Translation: Machine translation is usually used for translating a text or a speech of one natural language to another, for example, Google Translator.
  • Spelling Correction: Many software uses auto-correction for correcting typed sentences like MS Word, MS Powerpoint, Google Docs, etc. This is achieved through NLP.
  • Speech Recognition: Speech recognition is the conversion of spoken words into text. This can be implemented using NLP. It is vastly used in applications like dictating to MS Word, mobiles, voice user interface, home automation, and more.
  • Chatbot: NLP’s most important application is the implementation of chatbot. Nowadays, a chatbot is a necessary tool on every website that intends to know their customer better. Most companies have adopted this method for better growth.
  • Information Extraction: NLP is used for extracting structured data from semi-structured or unstructured machine-readable files. It is considered one of the critical applications of NLP.
  • Natural Language Understanding (NLU): NLU converts a large group of text to first-order logic structures, which is one of the formal representations that are easier for computers to understand and manipulate the notations of the natural language.

 

To build an NLP pipeline, you need to follow the following steps:

  • Sentence Segmentation
  • Word Tokenization
  • Stemming
  • Lemmatization
  • Identifying Stop Words
  • Dependency Parsing
  • POS Tags
  • Named Entity Recognition (NER)
  • Chunking
     

There are five phases of NLP, namely:
 

  • Lexical Analysis
  • Syntactic Analysis
  • Semantic Analysis
  • Discourse Integration
  • Pragmatic Analysis

 

Advantages of NLP include:
 

  • NLP helps users to get direct responses just by asking questions regarding any subject.
  • NLP provides appropriate answers to the questions asked. It avoids giving unnecessary information.
  • It helps machines to communicate with humans in their natural language.
  • It is very time efficient.
  • NLP is adopted by many companies, which helps them improve their efficiency of the documentation process, the accuracy of documentation, and the identification of the information from large datasets.

 

To explore more and learn NLP, get into Great Learning’s free NLP Courses, where on successful completion of the courses, you can secure your Certificates for free. 

Meet your faculty

Meet industry experts who will teach you relevant skills in artificial intelligence

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Sunil Kumar Vuppala

Director-Data Science
  • IIT Roorkee, IIM Ahmedabad alumnus with 20+ years of experience
  • Director at Ericsson specializing in AI, ML, and analytics

Frequently Asked Questions

What is NLP used for?

NLP helps machines to communicate with humans by analyzing, understanding and interpreting natural languages. It is used in many applications like speech recognition, translation, etc. It also enables devices to read text, hear them, analyze them, and determine the sentiments of the text.

What exactly is Natural Language Processing?

Natural Language Processing is a part of Computer Science, Artificial Intelligence, and Human Language. It is a technology that allows machines to understand, analyze, manipulate, and interpret human languages.

Are NLP courses worth it?

It takes a little of your time to find the right NLP course for learning. But it is worth it as NLP is a highly in-demand skill in industries. If you aim to become a developer, it will help you professionally if you know NLP.

How can I learn NLP for free?

You can find numerous NLP courses on the web that are provided for free. One such platform is Great Learning Academy, where you can search for NLP Free Courses, and you can also attain the certificate on successful completion of the courses.

What type of certification will I receive from these NLP courses?

These NLP courses offers a certificate of completion upon finishing, not a professional certification.

What is an NLP example?

Spam Detection is an example of NLP through which unwanted emails are avoided from entering the user’s inbox.

What is Natural Language Processing in Python?

Natural Language Processing (NLP) develops the services or applications that understand the human language. You can use the Python programming language to achieve such goals with its extensive library support. One such framework is Python’s NLTK package.