Best Online NLP Training, Courses

Doing online courses have become more and more widely adopted, in case you want to learn a new skill that will help with your work or project then this is what needs to be done. NLP ( Neuro Linguistic Programming ) started to grow as is used more and more ... Read moreBest Online NLP…

Doing online courses have become more and more widely adopted, in case you want to learn a new skill that will help with your work or project then this is what needs to be done. NLP (
Neuro Linguistic Programming ) started to grow as is used more and more in various projects and applications. In this article, you will learn what are the best online NLP training or courses that can be done.

What is NLP?

Per NLP.COM the definition is below?

NLP stands for Neuro-Linguistic Programming. Neuro refers to your neurology; Linguistic refers to language; programming refers to how that neural language functions. In other words, learning NLP is like learning the language of your own mind!

Best Online NLP Training, Course

There a couple of platforms like  UdemyCoursera or  where you can find online trainings not only for NLP but for everything you would think off. If you already have an account to them you can search and see what you can find as some of them like Coursera or  have a monthly subscription. Below is a list with the best ones that exists outhere:

1. Natural Language Processing with Deep Learning in Python

A complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets.

You will have 100 lectures in 12:48:00 hours of videos. The course was followed by 22,038 students and has a very good rating.

You will learn:

  • Understand and implement word2vec
  • Understand the CBOW method in word2vec
  • Understand the skip-gram method in word2vec
  • Understand the negative sampling optimization in word2vec
  • Understand and implement GloVe using gradient descent and alternating least squares
  • Use recurrent neural networks for parts-of-speech tagging
  • Use recurrent neural networks for named entity recognition
  • Understand and implement recursive neural networks for sentiment analysis
  • Understand and implement recursive neural tensor networks for sentiment analysis

Participant Review:

As someone who learns from scratch, I really enjoyed this approach of
this course. It’s always updated with the latest topics, and good even if you are advanced.
The instructor teaches the concepts with ease and clarity. You’ll also find the code to make the topics truly understandable.

2. Deep Learning: Advanced NLP and RNNs

Natural Language Processing with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!

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The course has 62 lectures and 08:01:55 hours off content. Is the highest rated in Udemy and followed by 6,078 students.

You will learn:

  • Build a text classification system (can be used for spam detection, sentiment analysis, and similar problems)
  • Build a neural machine translation system (can also be used for chatbots and question answering)
  • Build a sequence-to-sequence (seq2seq) model
  • Build an attention model
  • Build a memory network (for question answering based on stories)

Participant Review:

The best course in this series so far.
The lectures are thorough and easy to understand, maybe even for beginner
Still, it provides in-depth knowledge of NLP and RNNs to applications such as machine translation and chatbot.
It has a good balance between the math oriented
theory and the practical coding section.

Other Online Courses

3. Text Mining and Natural Language Processing in R

Hands-on text mining and natural language processing (NLP) training for data science applications in R .

This course has a more practical view and can help the ones who likes to scrap the internet. It has 79 lectures with 08:21:30 hours of content.

You will learn:

  • Students will be able to read in data from different sources- including databases
  • Basic webscraping– extracting text and tabular data from HTML pages
  • Social media mining from Facebook and Twitter
  • Extract information relating to tweets and posts
  • Analyze text data for emotions
  • Carry out Sentiment analysis
  • Implement natural language processing (NLP) on different types of text data

Participant Review:

Very practical course. I downloaded social media data using the concepts taught in this course to use in my project. The course really picked up pace after section 5

4. Data Science: Natural Language Processing (NLP) in Python

Practical Applications of NLP: spam detection, sentiment analysis, article spinners, and latent semantic analysis.

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A good course with 62 lectures and 07:58:05 hours of content. The course was followed by 20.000 students:

You will learn:

Who this course is for:

  • Students who are comfortable writing Python code, using loops, lists, dictionaries, etc.
  • Students 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
  • This course is NOT for those who find the tasks and methods listed in the curriculum too basic.
  • This course is NOT for those who don’t already have a basic understanding of machine learning and Python coding (but you can learn these from my FREE Numpy course).
  • This course is NOT for those who don’t know (given the section titles) what the purpose of each task is. E.g. if you don’t know what “spam detection” might be useful for, you are too far behind to take this course.

Participant Review:

Perfect course for introduction to NLP no matter what level you are currently.
With this course, it’s like a toolbox of NLP. You get to see how to apply some analysis methods and learn about the data.
You can be challenged in the course even if you’re an expert. There’s always more to learn.

5. Hands On Natural Language Processing (NLP) using Python

Learn Natural Language Processing ( NLP ) & Text Mining by creating text classifier, article summarizer, and many more.

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What you’ll learn

  • Understand the various concepts of natural language processing along with their implementation
  • Build natural language processing based applications
  • Learn about the different modules available in Python for NLP
  • Create personal spam filter or sentiment predictor
  • Create personal text summarizer

Participant Review

The python overview is very good. I was not expecting to learn much but I picked up on many tricks. I also thought the NLP was very comprehensive and easy to understand. I will say I think this course might be difficult to undertstand for someone who has never coded in python before.

6. Natural Language Processing (Coursera)

This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few. Upon completing, you will be able to recognize NLP tasks in your day-to-day work, propose approaches, and judge what techniques are likely to work well. The final project is devoted to one of the most hot topics in today’s NLP. You will build your own conversational chat-bot that will assist with search on StackOverflow website. The project will be based on practical assignments of the course, that will give you hands-on experience with such tasks as text classification, named entities recognition, and duplicates detection

Approx. 34 hours to complete

Suggested: 5 weeks of study, 4-5 hours per week

7. NLP with Python for Machine Learning Essential Training (linkedin)

What you’ll learn

  • What are NLP and NLTK?
  • Using regular expressions
  • Using stemming and lemmatizing
  • Methods to vectorize raw data
  • Building and evaluating machine learning classifiers