11 Best Natural Language Processing Courses Online in 2024

Are you looking for Best Natural Language Processing Courses Online?. If yes, then your search will end after reading this article. In this article, you will find the 11 Best Natural Language Processing Courses Online. So, give your few minutes to this article and find out the Best Natural Language Processing Courses Online.

Courses List-

Natural Language Processing is getting popular due to its tremendous applications. Nowadays, you can see the strength of NLP in various fields. For example, Google’s Assistant, Amazon Alexa, Apple’s Siri, and Cortana all are based on NLP. Chatbot and Sentiment Analysis are also the most popular application of NLP.

Most of the industries are using Natural Language Processing. There are various jobs available in Natural Language Processing. Many companies are hiring NLP Engineers. So, if you are the one who wants to learn Natural Language Processing, then definitely you have a question in your mind-

How to master Natural Language Processing Skills?

Right?

So, to learn NLP, you can refer to NLP Books or NLP online Courses.

Now, you might be thinking about which books or courses are good for NLP?

So, don’t worry. I will help you to choose the best NLP Online Courses and Books. I have already written an article for Best NLP Books. If you want to prefer books for learning NLP, then you should read this article- Best Books for Natural Language Processing You Should Read

But if you like online courses to learn NLP, then give your few minutes to this article. In this article, I will discuss some Best Natural Language Processing Courses Online.

I have filtered these courses on the following criteria-

Criteria-

1. Rating of these Courses.
2. Coverage of Natural Language Processing Topics.
3. Engaging trainer and Interesting lectures.
4. Number of Students Benefitted.
5. Good Reviews from various aggregators and forums.

On these criteria, I filtered out Courses from Different platforms like Coursera, Udemy, Udacity, Edureka, Codecademy, edX.

Now, without any further ado, let’s start finding the Best Natural Language Processing Courses Online for you.

Best Natural Language Processing Courses Online

1. Natural Language Processing Specialization– Coursera

Provider- deeplearning.ai

Rating- 4.6/5

Time to Complete- 4 months( If you spend 6 hours per week)

This is a specialization program offered by deeplearning.ai. In this specialization program, you will learn from two experts in NLP, Younes Bensouda Mourri and Łukasz Kaiser.

This specialization program is more focused on practical base learning and you will learn how to build NLP applications that perform question-answering and sentiment analysis. You will also learn how to build tools to translate languages, chatbots, etc.

For implementing sentiment analysis, you will use logistic regression, naïve Bayes, and word vectors. And to perform advanced sentiment analysis, text generation, named entity recognition, you will use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow and Trax.

In this specialization program, there are 4 courses. Now let’s see the courses-

Courses Details-

1. Natural Language Processing with Classification and Vector Spaces
2. Natural Language Processing with Probabilistic Models
3. Natural Language Processing with Sequence Models
4. Natural Language Processing with Consideration Models

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have a working knowledge of machine learning, intermediate Python including experience with a deep learning framework such as TensorFlow and Keras.
• Along with this, you should have knowledge of calculus, linear algebra, and statistics.

Interested to Enroll?

If yes, then get more details here- Natural Language Processing Specialization

2. Become a Natural Language Processing Expert– Udacity

Rating- 4.5/5

Time to complete- 3 months (If you spend 10-15 hours per week)

In this Nano-degree program, you will learn cutting-edge natural language processing techniques to process speech and analyze text.

In this program, you will also build probabilistic and deep learning models, such as hidden Markov models and recurrent neural networks, to teach the computer to do tasks such as speech recognition, machine translation, and more.

This Nanodegree program will teach you how to use several techniques, including table lookups, n-grams, and hidden Markov models, to tag parts of speech in sentences, and compare their performance.

There are 3 courses in this Nano Degree Program. Let’s see the details of the courses-

Courses List-

1. Introduction to Natural Language Processing
2. Computing with Natural Language
3. Communicating with Natural Language

Extra Benefits-

• You will get a chance to work on Real-world projects with Industry Experts.
• You will get Technical mentor support, Github review, etc.

Who Should Enroll?

• Those who have Intermediate Knowledge of Python, Statistics, Machine Learning, & Deep Learning.

Interested to Enroll?

If yes, then get more details here-Become a Natural Language Processing Expert

3. Natural Language Processing– Coursera

Provider- National Research University Higher School of Economics

Rating- 4.5/5

Time to Complete- 32 Hours

This is one of the best Online Courses available for NLP. This course covers a wide range of topics in Natural Language Processing. Starting from sentiment analysis, summarization, dialogue state tracking, and many more.

In this course, you will build your own conversational chatbot that will assist with search on the StackOverflow website. Now, let’s see what topics are covered in this Course-

Topics Covered-

• Intro and text classification
• Language modeling and sequence tagging
• Vector Space Models of Semantics
• Sequence to sequence tasks
• Dialog systems

This course is part of Advanced Machine Learning Specialization.

Extra Benefits-

• You will get a Shareable Certificate.
• Along with that, you will build a conversational chat-bot.

Who Should Enroll?

• This course requires basic knowledge of linear algebra and probability theory, machine learning setup, and deep neural networks.

Interested to Enroll?

If yes, then get more details here- Natural Language Processing

4. Natural Language Processing in TensorFlow– Coursera

Provider- deeplearning.ai

Rating- 4.6/5

Time to Complete- 14 Hours

This is another most popular course available for Natural language processing. This course is part of TensorFlow in Practice Specialization. In this course, you will build natural language processing systems using TensorFlow. TensorFlow is a popular open-source framework for machine learning.

Along with this, you will learn how to process text, including tokenizing and representing sentences as vectors, so that they can be input into a neural network.

You will also learn techniques like RNN, GRU, LSTM, and more. In this course, you will work on training LSTMs on existing text to create original poetry and more. The reason I love this course is its practical presentation. You will not get bored during this course.

Now, let’s see what topics are covered in that course-

Topics Covered-

• Sentiment in text
• Word Embeddings
• Sequence models
• Sequence models and literature

Extra Benefits-

• You will get a Shareable Certificate.
• You will work on hands-on assignments and projects that will enhance your portfolio.
• Along with that, you will get to solve Practice Quizzes and Graded Assignments.

Who Should Enroll?

• Those who have intermediate-level knowledge in Python, high school level mathematics knowledge, and those who are familiar with TensorFlow.

So, if you have the following knowledge, then only you should enroll yourself in this course. But if you want to get a complete understanding of TensorFlow, then you can enroll in this Specialization program- TensorFlow in Practice Specialization

Interested to Enroll?

If yes, then get more details here- Natural Language Processing in TensorFlow

5. Introduction to Natural Language Processing in Python– DataCamp

Time to Complete- 4 hours

This Natural Language Processing Course is offered by DataCamp. In this course, you’ll learn natural language processing (NLP) basics, such as how to identify and separate words, how to extract topics in a text, and how to build your own fake news classifier.

You’ll also learn how to use basic libraries such as NLTK, alongside libraries that utilize deep learning to solve common NLP problems. Now, let’s see the topics covered in this course-

Topics Covered-

• Regular expressions & word tokenization
• Simple topic identification
• Named-entity recognition
• Building a “fake news” classifier

Who Should Enroll?

• Those who have working knowledge in Python.

Interested to Enroll?

If yes, then get more details here- Introduction to Natural Language Processing in Python

6. Natural Language Processing with Deep Learning in Python –Udemy

Rating- 4.5/5

Provider- Lazy Programmer

Time to Complete- 12 hours

In this course, you will learn NLP (natural language processing) with deep learning. This course will teach you word2vec and how to implement word2vec.

You will also learn how to implement GloVe using gradient descent and alternating least squares. This course uses recurrent neural networks for named entity recognition. Along with that, you will learn how to implement recursive neural tensor networks for sentiment analysis. Let’s see the topics covered in this course-

Topics Covered-

1. Outline, Review, and Logistical Things.
2. Beginner’s corner- Working with word vectors.
3. Review of Language Modeling and Neural Networks.
4. Word Embedding and Word2Vec.
5. Word Embedding using GloVe.
6. Unifying Word2Vec and GloVe.
7. Using a Neural Network to solve NLP problems.
8. Recursive Neural Network
9. Theano and Tensorflow Basics Review.

Extra Benefits-

• You will get a Certificate of Completion.
• Along with that, you will get full-time access to course material.

Who Should Enroll?

• Those who have knowledge of calculus, matrix addition, multiplication, and, probability and comfortable with Python coding, and Numpy coding.
• If someone has knowledge of neural networks and backpropagation.
• Those who can write feedforward neural network in Theano or TensorFlow and recurrent neural network / LSTM / GRU in Theano or TensorFlow.

Interested to Enroll?

If yes, then get more details here- Natural Language Processing with Deep Learning in Python 

7. Applied Text Mining in Python– Coursera

Provider- University of Michigan

Rating- 4.3/5

Time to Complete- 29 hours

This course starts with the understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text.

In that course, you will learn how to apply basic natural language processing methods. You will also learn to write code that groups documents by topic. This course is part of Applied Data Science with Python Specialization

.

Now, let’s see the topics covered in that course-

Topics Covered-

• Working with Text in Python
• Basic Natural Language Processing
• Classification of Text
• Topic Modeling

Extra Benefits-

• You will get a Shareable Certificate.
• Along with that, you will get to solve Practice Quizzes and Graded Assignments.

Who Should Enroll?

• Those who have intermediate-level knowledge in Python, Machine Learning, Plotting, Charting & Data Representation in Python.

So, if you have the following knowledge, then only you should enroll yourself in this course. But if you don’t have, then you can enroll yourself in this specialization program- Applied Data Science with Python Specialization. This specialization program will also cover this course- Applied Text Mining in Python.

Interested to Enroll?

If yes, then get more details here-  Applied Text Mining in Python

8. Learn Natural Language Processing- Codecademy

Time to Complete- 10 hours

This online course is offered by Codecademy. This course will provide an overview of the main NLP concepts and teach you how to build a Python chatbot. In this course, you will work on three projects-

• Read the News Analysis
• Mystery Friend.
• Natural Language Parsing Analysis

Now, let’s see the topics covered in this course-

• Getting Started with Natural Language Processing.
• Introduction to Regular Expressions
• Text Preprocessing
• Language Parsing
• Bag-of-Words Language Model
• Term Frequency-Inverse Document Frequency
• Word Embeddings
• Deep Learning and Text Generation

Extra Benefits-

• You will earn a Certificate of completion.
• And you will create portfolio projects that showcase your new skills.

Who Should Enroll?

• There is no other prerequisite to enroll in this course, you should have only Python 3 Knowledge.
• If you don’t have Python Knowledge, then you can enroll in this course of Python 3- Learn Python 3

Interested to Enroll?

If yes, then get more details here-  Learn Natural Language Processing

9. Data Science: Natural Language Processing (NLP) in Python –Udemy

Rating- 4.5/5

Provider- Lazy Programmer

Time to Complete- 10 hours

In this course, you will build multiple practical systems using natural language processing, or NLP. This course is best if you want to build applications of NLP. Because in this course, you will learn how to build a cipher decryption algorithm, spam detector, model for sentiment analysis in Python, and article spinner.

So, this course is all about how to create applications in NLP. This course doesn’t focus on the theoretical part of NLP, the main objective of this course is to give an experimental overview of NLP.

Now, let’s see the topics covered in this course-

Topics Covered-

• Natural Language Processing- What is it used for?
• Decrypting Ciphers.
• Build your own Spam Detector.
• Build your own Sentiment analyzer.
• NLTK Exploration.
• Latent Semantic Analysis.
• Write your own article spinner.
• How to learn more about NLP.
• Machine Learning Basic Review.

Extra Benefits-

• You will get a Certificate of Completion.
• Along with that, you will get full-time access to course material.

Who Should Enroll?

This course is suitable for-

• Students who are comfortable writing Python code and who want to learn more about machine learning but don’t want to do a lot of math.
• Professionals who are interested in applying machine learning and NLP to practical problems like spam detection, Internet marketing, and sentiment analysis

Interested to Enroll?

If yes, then get more details here- Data Science: Natural Language Processing (NLP) in Python

10. NLP -Natural Language Processing with Python- Udemy

Rating- 4.5/5

Provider- Jose Portilla

Time to Complete- 11.5 hours

This course is listed as Bestseller in Udemy. And that is correct because this course is a complete online resource for learning how to use Natural Language Processing with the Python programming language.

This course covers everything you need to learn in order to become a world-class practitioner of NLP with Python. In this course, you will learn how to work with Text Files with Python. In this course, you will utilize Regular Expressions for pattern searching in text.

Now, let’s see the topics covered in this course-

Topics Covered-

• Python Text Basics.
• Natural Language Processing Basics.
• Part of Speech Tagging and Named Entity Recognition.
• Text Classification.
• Semantics and Sentiment Analysis.
• Topic Modeling.
• Deep Learning for NLP.

Extra Benefits-

• You will get a Certificate of Completion.
• You will also get 2 articles and 2 downloadable resources.
• Along with that, you will get full-time access to course material.

Who Should Enroll?

• There is not too many requirements for enrolling in this course. Only those who know Python and want to learn NLP can enroll.

Interested to Enroll?

If yes, then get more details here- NLP -Natural Language Processing with Python

11. Natural Language Processing with Python Certification Course- Edureka

Rating- 4.3/5

Mode of Learning- Live Classes

Edureka provides Live Classes based on your convenience. This course will teach you the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. In this course, you will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing, and so on using Python’s most famous NLTK package.

After learning all these concepts, you will learn to build your own text classifier using the Naïve Bayes algorithm. This course has been packed up with a lot of real-life examples, where you can apply the learned content to use. Such as Semantic Analysis, Text Processing, Sentiment Analytics, and Machine Learning.

This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language.

Now, let’s see the topics covered in this course-

Topics Covered-

• Introduction to Text Mining and NLP
  • Hands-On/Demo:
    • Install NLTK Packages using NLTK Downloader
    • Accessing your operating system using the OS Module in Python
    • Reading & Writing .txt Files from/to your Local
    • Reading & Writing .docx Files from/to your Local
    • Working with the NLTK Corpora
• Extracting, Cleaning, and Pre-processing Text
  • Hands-On/Demo:
    • Tokenization: Regex, Word, Blank line, Sentence Tokenizers
    • Bigrams, Trigrams & Ngrams
    • Stopword Removal
    • POS Tagging
    • Named Entity Recognition (NER)
• Analyzing Sentence Structure
  • Hands-On/Demo:
    • Parsing Syntax Trees
    • Chunking
    • Chinking
    • Automate Text Paraphrasing using CFG’s
• Text Classification – I
  • Hands-On/Demo:
    • Demonstrate Bag of Words Approach
    • Working with CountVectorizer()
    • Using TF & IDF
• Text Classification – II
  • Hands-On/Demo:
    • Converting text to features and labels
    • Demonstrate text classification using Multinomial NB Classifier
    • Leveraging Confusion Matrix
• In-Class Project
  • Hands-On:
    • Sentiment Analysis

Extra Benefits-

• You will get Edureka’s Natural Language Processing Engineer Certificate.
• You get lifetime access to the course materials, presentations, quizzes, and installation guide.
• You will also get 60 days of Cloud Lab access
• Along with that, you will get 24 x 7 Expert Support.
• You will get a chance to work on practical assignments after each class.
• You will also get a chance to work on Live projects.

Who Should Enroll?

• Those who have knowledge of Python programming and a good understanding of Machine Learning concepts.

Interested to Enroll?

If yes, then get more details here-Natural Language Processing with Python Certification Course

So these are the 11 Best Natural Language Processing Courses Online.

Guided Projects on NLP

The more projects are listed in your portfolio, the more privilege you will get. That’s why I have chosen some guided projects on NLP for you.

Let’s have a look-

1. Perform Sentiment Analysis with scikit-learn

In this project-based course, you will learn the fundamentals of sentiment analysis, and build a logistic regression model to classify movie reviews as either positive or negative. You will also learn the cleaning and preprocessing of text data.

You will also learn how to perform feature extraction with The Natural Language Toolkit (NLTK) and tuning model hyperparameters and evaluate model accuracy.

This course runs on Coursera’s hands-on project platform called Rhyme.

Time to Complete- 2 Hours

Who can Enroll- Who has basic knowledge of Python and Machine Learning.

So, if you are interested, you can check here- Perform Sentiment Analysis with scikit-learn

2. Named Entity Recognition using LSTMs with Keras

In this 1-hour long project-based course, you will use the Keras API with TensorFlow as its backend to build and train a bidirectional LSTM neural network model to recognize named entities in text data.

Named entity recognition models can be used to identify mentions of people, locations, organizations, etc. In that project-based course, you will Solve the Named Entity Recognition (NER) problem with LSTMs.

Time to Complete- 1.5 Hours

Who can Enroll- Those who have knowledge of Python and theoretical understanding of Neural networks.

There are some more Projects available, you can check-

• Sentiment Analysis with Deep Learning using BERT
• Language Classification with Naive Bayes in Python
• Anomaly Detection in Time Series Data with Keras

So, these are some guided projects, that you can consider. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover the 11 Best Natural Language Processing Courses Online. If you have any doubt or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

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– Henry Ford