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Free NLP Courses

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Introduction to Natural Language Processing
star   4.53 47.2K+ Learners 4.5 hrs

Skills: Natural Language Processing (NLP), Language Models, TextBlob, Sentiment Analysis, Semantic Segmentation

FREE
How to Build your own Chatbot using Python?
star   4.51 40.3K+ Learners 1.5 hrs

Skills: Python, Natural Language Processing, chatbot architecture, use of libraries (e.g. NLTK, transformers), APIs, user interaction logic

FREE
Natural Language Processing Projects
star   4.61 8.4K+ Learners 2.5 hrs

Skills: NLP Use-cases, NLP Project

FREE
Machine Translation
star   4.53 5.1K+ Learners 1.5 hrs

Skills: What is RNN, Sequence, Solving a use case , Translation from English text to French

FREE
Generative AI with Machine Learning and LLMs
star   4.71 411 Learners 1.5 hrs

Skills: Generative AI Fundamentals, Supervised vs Unsupervised Learning, Discriminative vs Generative AI, Evolution of Generative AI, Generative AI Models, Real-World GenAI Applications, Large Language Models (LLMs), Text Understanding in AI, Next-Word Prediction

FREE
ChatGPT for NLP
star   4.51 6.4K+ Learners 0.5 hr

Skills: Introduction to Text Summarization, Generating Text Summarization Code in ChatGPT, Understanding Text Summarization Code

FREE
Sentiment Analysis using Python
star   4.48 20.2K+ Learners 1.5 hrs

Skills: Text Pre-processing,Vectorization,Modeling,Amazon Reviews Sentiment Analysis,Twitter Sentiment Analysis

FREE
Introduction to Text Mining
star   4.67 1.4K+ Learners 1 hr

Skills: Introduction to Text Mining, Cleaning Data, Hierarchical Clustering in Text Analytics

FREE
Textblob
star   4.58 1.8K+ Learners 1.5 hrs

Skills: NLP Basics, TextBlob Introduction, Functionalities of Textblob, Textblob Sentiment Analysis

FREE
NLP Customer Experience
star   4.52 4.2K+ Learners 1 hr

Skills: Customer Engagement, NLP, Social Media Analytics

free icon FREE
Introduction to Natural Language Processing
star   4.53 47.2K+ Learners 4.5 hrs

Skills: Natural Language Processing (NLP), Language Models, TextBlob, Sentiment Analysis, Semantic Segmentation

free icon FREE
How to Build your own Chatbot using Python?
star   4.51 40.3K+ Learners 1.5 hrs

Skills: Python, Natural Language Processing, chatbot architecture, use of libraries (e.g. NLTK, transformers), APIs, user interaction logic

pro icon PRO
End-to-End NLP with Python: Build Chatbots and LLM Applications
free icon FREE
Natural Language Processing Projects
star   4.61 8.4K+ Learners 2.5 hrs

Skills: NLP Use-cases, NLP Project

free icon FREE
Machine Translation
star   4.53 5.1K+ Learners 1.5 hrs

Skills: What is RNN, Sequence, Solving a use case , Translation from English text to French

free icon FREE
Generative AI with Machine Learning and LLMs
star   4.71 411 Learners 1.5 hrs

Skills: Generative AI Fundamentals, Supervised vs Unsupervised Learning, Discriminative vs Generative AI, Evolution of Generative AI, Generative AI Models, Real-World GenAI Applications, Large Language Models (LLMs), Text Understanding in AI, Next-Word Prediction

free icon FREE
ChatGPT for NLP
star   4.51 6.4K+ Learners 0.5 hr

Skills: Introduction to Text Summarization, Generating Text Summarization Code in ChatGPT, Understanding Text Summarization Code

free icon FREE
Sentiment Analysis using Python
star   4.48 20.2K+ Learners 1.5 hrs

Skills: Text Pre-processing,Vectorization,Modeling,Amazon Reviews Sentiment Analysis,Twitter Sentiment Analysis

free icon FREE
Introduction to Text Mining
star   4.67 1.4K+ Learners 1 hr

Skills: Introduction to Text Mining, Cleaning Data, Hierarchical Clustering in Text Analytics

free icon FREE
Textblob
star   4.58 1.8K+ Learners 1.5 hrs

Skills: NLP Basics, TextBlob Introduction, Functionalities of Textblob, Textblob Sentiment Analysis

free icon FREE
NLP Customer Experience
star   4.52 4.2K+ Learners 1 hr

Skills: Customer Engagement, NLP, Social Media Analytics

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. 

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Generative AI with Machine Learning and LLMs
star   4.71 411 Learners 1.5 hrs

Skills: Generative AI Fundamentals, Supervised vs Unsupervised Learning, Discriminative vs Generative AI, Evolution of Generative AI, Generative AI Models, Real-World GenAI Applications, Large Language Models (LLMs), Text Understanding in AI, Next-Word Prediction

FREE
Introduction to Text Mining
star   4.67 1.4K+ Learners 1 hr

Skills: Introduction to Text Mining, Cleaning Data, Hierarchical Clustering in Text Analytics

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Introduction to Natural Language Processing
star   4.53 47.2K+ Learners 4.5 hrs

Skills: Natural Language Processing (NLP), Language Models, TextBlob, Sentiment Analysis, Semantic Segmentation

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How to Build your own Chatbot using Python?
star   4.51 40.3K+ Learners 1.5 hrs

Skills: Python, Natural Language Processing, chatbot architecture, use of libraries (e.g. NLTK, transformers), APIs, user interaction logic

FREE
Sentiment Analysis using Python
star   4.48 20.2K+ Learners 1.5 hrs

Skills: Text Pre-processing,Vectorization,Modeling,Amazon Reviews Sentiment Analysis,Twitter Sentiment Analysis

FREE
Natural Language Processing Projects
star   4.61 8.4K+ Learners 2.5 hrs

Skills: NLP Use-cases, NLP Project

FREE
ChatGPT for NLP
star   4.51 6.4K+ Learners 0.5 hr

Skills: Introduction to Text Summarization, Generating Text Summarization Code in ChatGPT, Understanding Text Summarization Code

FREE
Machine Translation
star   4.53 5.1K+ Learners 1.5 hrs

Skills: What is RNN, Sequence, Solving a use case , Translation from English text to French

FREE
NLP Customer Experience
star   4.52 4.2K+ Learners 1 hr

Skills: Customer Engagement, NLP, Social Media Analytics

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Textblob
star   4.58 1.8K+ Learners 1.5 hrs

Skills: NLP Basics, TextBlob Introduction, Functionalities of Textblob, Textblob Sentiment Analysis

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Generative AI with Machine Learning and LLMs
star   4.71 411 Learners 1.5 hrs

Skills: Generative AI Fundamentals, Supervised vs Unsupervised Learning, Discriminative vs Generative AI, Evolution of Generative AI, Generative AI Models, Real-World GenAI Applications, Large Language Models (LLMs), Text Understanding in AI, Next-Word Prediction

FREE
Introduction to Text Mining
star   4.67 1.4K+ Learners 1 hr

Skills: Introduction to Text Mining, Cleaning Data, Hierarchical Clustering in Text Analytics

Popular

FREE
Introduction to Natural Language Processing
star   4.53 47.2K+ Learners 4.5 hrs

Skills: Natural Language Processing (NLP), Language Models, TextBlob, Sentiment Analysis, Semantic Segmentation

FREE
How to Build your own Chatbot using Python?
star   4.51 40.3K+ Learners 1.5 hrs

Skills: Python, Natural Language Processing, chatbot architecture, use of libraries (e.g. NLTK, transformers), APIs, user interaction logic

FREE
Sentiment Analysis using Python
star   4.48 20.2K+ Learners 1.5 hrs

Skills: Text Pre-processing,Vectorization,Modeling,Amazon Reviews Sentiment Analysis,Twitter Sentiment Analysis

FREE
Natural Language Processing Projects
star   4.61 8.4K+ Learners 2.5 hrs

Skills: NLP Use-cases, NLP Project

FREE
ChatGPT for NLP
star   4.51 6.4K+ Learners 0.5 hr

Skills: Introduction to Text Summarization, Generating Text Summarization Code in ChatGPT, Understanding Text Summarization Code

FREE
Machine Translation
star   4.53 5.1K+ Learners 1.5 hrs

Skills: What is RNN, Sequence, Solving a use case , Translation from English text to French

FREE
NLP Customer Experience
star   4.52 4.2K+ Learners 1 hr

Skills: Customer Engagement, NLP, Social Media Analytics

FREE
Textblob
star   4.58 1.8K+ Learners 1.5 hrs

Skills: NLP Basics, TextBlob Introduction, Functionalities of Textblob, Textblob Sentiment Analysis

Learner reviews of the Free NLP Courses

Our learners share their experiences of our courses

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Reviewer Profile

5.0

★★★★ ★
India
“Introduction to Natural Language Processing”
This course offers a comprehensive understanding of cutting-edge techniques in Natural Language Processing (NLP) and machine learning. With hands-on projects, expert insights, and practical applications, students will develop essential skills to excel in the field. By mastering NLP, learners can unlock new career opportunities in technology and data analysis.
Reviewer Profile

5.0

★★★★ ★
India
“Introduction to Natural Language Programming”
Natural Language Processing (NLP) is a captivating field that merges computer science, artificial intelligence, and linguistics to enable computers to understand, interpret, and generate human language meaningfully. It involves teaching machines to comprehend the complexities of language, which can include nuances, idioms, and context. This understanding facilitates applications such as chatbots, voice assistants, and translation services.
Reviewer Profile

5.0

★★★★ ★
India
“A Comprehensive and Engaging Learning Experience”
The course was well-structured, and the curriculum was very thorough. The instructor's explanations were clear and engaging, making complex topics easier to understand. The depth of the topics covered was impressive, and the course was easy to follow from start to finish. The quizzes and assignments were well-designed to reinforce learning.
Reviewer Profile

5.0

★★★★ ★
India
“Introduction to Natural Language Preprocessing”
This course helped me a lot to learn new skills about NLP, and the instructors' explanations were also good.
Reviewer Profile

4.0

★★★ ★ ☆
India
“Grateful for the Enriching Experience! The Comprehensive Approach and Attention to Detail in the Materials Made This One of the Best Learning Sessions I've Attended”
Thoroughly enjoyed the session! The interactive format and practical examples made complex concepts easy to understand. Kudos to the team for an outstanding job.
Reviewer Profile

5.0

★★★★ ★
India
“It Was Learning Better for Future and Good Course”
I had an excellent experience with Great Learning. The course was well-structured, and the content was thorough and engaging. The instructors were highly knowledgeable and provided clear explanations. The hands-on projects and assignments helped solidify my understanding of the concepts. I appreciated the flexibility of online learning, which allowed me to learn at my own pace. The support from the community and mentors was fantastic, making it easier to navigate any challenges.
Reviewer Profile

5.0

★★★★ ★
India
“Introduction to Natural Language Processing”
Introduction to Natural Language Processing was learned easily.
Reviewer Profile

5.0

★★★★ ★
India
“NLP Engineer, NLP Researcher, NLP Analyst, Language Engineer, and Text Analyst”
NLP titles encompass a broad range of roles that involve developing and applying natural language processing techniques to solve real-world problems. Some examples of NLP titles include NLP Engineer, NLP Researcher, NLP Analyst, Language Engineer, Text Analyst, and Conversational AI Designer.
Reviewer Profile

5.0

★★★★ ★
“This Course Provides Students with the Opportunity to Critically Evaluate Models of Machine Learning”
It pays particular attention to their performance, interpretability, fairness, and readiness for deployment. Whether you are a data researcher, manager, or technical participant, this course will provide you with the tools to ensure reliable, ethical, and aligned ML systems with business objectives.
Reviewer Profile

5.0

★★★★ ★
India
“Comprehensive and Well-Structured Introduction to NLP”
I liked the way the concepts were taught in-depth, giving a better foundation to NLP.

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.