If you want to read the original article, click here NLP Courses Online (Natural Language Processing).
NLP Courses Online, Natural Language Processing is becoming increasingly popular as a result of its numerous uses. The power of NLP may now be seen in a variety of industries.
Subscribe to our newsletter!
NLP is used in Google Assistant, Amazon Alexa, Apple Siri, and Microsoft Cortana, for example. NLP’s most common applications include chatbots and sentiment analysis.
Natural Language Processing has a variety of work opportunities. Many businesses are looking for NLP engineers.
So, if you’re interested in learning Natural Language Processing, you’ve probably got a question on your mind!
You might be wondering which courses are good for NLP at this point?.
Will assist you in selecting the greatest NLP Online Courses available. If you prefer online courses to learn NLP, however, take a few minutes to read this post.
NLP Courses Online
This article will go through some of the best online natural language processing courses.
Deeplearning.ai offers a specialized program in this area. Younes Bensouda Mourri and Ukasz Kaiser, two NLP professionals, will teach you in this specialty program.
You will learn how to construct NLP apps that do question-answering and sentiment analysis in this specialty program, which is primarily focused on practical-based learning.
You’ll also learn how to create language translators, chatbots, and other tools.
You’ll utilize logistic regression, naive Bayes, and word vectors to implement sentiment analysis.
In TensorFlow and Trax, you’ll employ dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks to do sophisticated sentiment analysis, text generation, and named entity identification.
Natural Language Processing with Classification and Vector Spaces
Natural Language Processing with Probabilistic Models
Natural Language Processing with Sequence Models
Natural Language Processing with Consideration Models
This Nano-degree program will teach you how to process speech and analyze text using cutting-edge natural language processing techniques.
You’ll also learn how to use probabilistic and deep learning models, such as hidden Markov models and recurrent neural networks, to teach a computer to do tasks like speech recognition and machine translation.
This Nanodegree program will teach you how to tag bits of speech in phrases and compare their performance using a variety of approaches like table lookups, n-grams, and hidden Markov models.
Introduction to Natural Language Processing
Computing with Natural Language
Communicating with Natural Language
This is one of the most comprehensive online NLP courses accessible. This course covers a broad spectrum of Natural Language Processing subjects. Sentiment analysis, summarization, discussion state tracking, and many other features are available.
This course will teach you how to create your own conversational chatbot that will help you find answers on the StackOverflow website. Let’s have a look at the subjects covered in this course. –
Intro and text classification
Language modeling and sequence tagging
Vector Space Models of Semantics
Sequence to sequence tasks
This course begins with an explanation of how python handles text, the structure of text for both machines and people, and an overview of the nltk text manipulation framework.
You will learn how to apply basic natural language processing technologies in that course. You’ll also learn how to develop code that organizes documents into categories.
This course is part of the Python Specialization in Applied Data Science.
Working with Text in Python
Basic Natural Language Processing
Classification of Text
Codecademy provides this online course. This course will show you how to develop a Python chatbot while also providing an overview of the basic NLP topics.
You will work on three projects in this course:
- Read the News Analysis
- Mystery Friend.
- Natural Language Parsing Analysis
Getting Started with Natural Language Processing.
Introduction to Regular Expressions
Bag-of-Words Language Model
Term Frequency-Inverse Document Frequency
Deep Learning and Text Generation
This is one of the most comprehensive online NLP courses accessible. This course covers a broad spectrum of Natural Language Processing subjects.
Sentiment analysis, summarization, discussion state tracking, and many other features are available.
This course will teach you how to create your own conversational chatbot that will help you find answers on the StackOverflow website.
Another popular course for Natural Language Processing is this one. TensorFlow in Practice Specialization includes this course.
You will use TensorFlow to create natural language processing systems in this course. TensorFlow is a prominent open-source machine learning framework.
You’ll also learn how to analyze text, including how to tokenize and encode phrases as vectors so they can be fed into a neural network.
You’ll also learn RNN, GRU, LSTM, and other approaches. You will focus on training LSTMs on current material to generate creative poetry and more in this course.
Sentiment in text
Sequence models and literature
DataCamp is offering a Natural Language Processing course. This course will teach you the fundamentals of natural language processing (NLP), including how to recognize and separate words, extract topics from a document, and create your own fake news classifier.
You’ll also learn how to use fundamental libraries like NLTK, as well as deep learning libraries to solve typical NLP challenges. Let’s take a look at the subjects covered in this course:
Regular expressions & word tokenization
Simple topic identification
Building a “fake news” classifier
This course will teach you how to use deep learning to learn NLP (natural language processing). This course will educate you about word2vec and how to use it.
You’ll also learn how to use gradient descent and alternating least squares to construct GloVe. For named entity recognition, recurrent neural networks are used in this course.
You’ll also learn how to use recursive neural tensor networks to perform sentiment analysis. Let’s have a look at the topics covered in this class.
Outline, Review, and Logistical Things.
Beginner’s corner- Working with word vectors.
Review of Language Modeling and Neural Networks.
Word Embedding and Word2Vec.
Word Embedding using GloVe.
Unifying Word2Vec and GloVe.
Using a Neural Network to solve NLP problems.
Recursive Neural Network
Theano and Tensorflow Basics Review.
Using natural language processing, or NLP, you will design several practical systems in this course. If you want to design NLP applications, this is the course for you.
Because you’ll learn how to create a cipher decryption method, a spam detector, a Python model for sentiment analysis, and an article spinner in this course.
As a result, the focus of this course is on how to construct NLP applications. This course does not focus on the theoretical aspects of NLP; rather, it aims to provide an experimental overview of NLP.
Natural Language Processing- What is it used for?
Build your own Spam Detector.
Build your own Sentiment analyzer.
Latent Semantic Analysis.
Write your own article spinner.
How to learn more about NLP.
Machine Learning Basic Review.
Udemy lists this course as a Best Seller. This is right because this course provides a comprehensive online resource for learning how to apply Natural Language Processing with Python.
This course will teach you all you need to know to become a world-class Python NLP practitioner. This course will teach you how to use Python to work with Text Files.
Regular Expressions will be used to search for patterns in text in this course.
Python Text Basics.
Natural Language Processing Basics.
Part of Speech Tagging and Named Entity Recognition.
Semantics and Sentiment Analysis.
Deep Learning for NLP.
It takes practice to learn something new. So, if you want to practice NLP, working on projects is the best way to go.
The more projects you have in your portfolio, the more benefits you’ll receive. That is why I have selected several guided NLP assignments for you.
You will master the principles of sentiment analysis and create a logistic regression model to classify movie reviews as positive or negative in this project-based course. Cleaning and preparing text data will also be covered.
You’ll also learn how to use The Natural Language Toolkit (NLTK) to do feature extraction, tune model hyperparameters, and evaluate model correctness.
This course uses Rhyme, Coursera’s hands-on project platform.
In this 1-hour project-based course, you’ll create and train a bidirectional LSTM neural network model to recognize named things in text data using the Keras API and TensorFlow as the backend.
People, places, and organizations can all be identified using named entity recognition models. You will use LSTMs to solve the Named Entity Recognition (NER) problem in that project-based course.
To read more visit NLP Courses Online (Natural Language Processing).
If you are interested to learn more about data science, you can find more articles here finnstats.