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Learn Natural Language Processing with Online Courses and Programs

Computers understand human language through natural language processing (NLP). Explore how to learn natural language processing with online NLP courses delivered through edX.

What is natural language processing?

If you’ve asked Siri or Alexa for the weather report, used voice GPS in your car, or interacted with a chatbot on a website, you’ve used a natural language processing program. 

Natural language processing is a branch of artificial intelligence centered around teaching computers to understand text and spoken language. Through statistical machine learning and deep learning models, computer scientists can train a computer to read, analyze, and generate language.Footnote 1

NLP tasks are difficult because human language does not follow a strict set of rules and often includes many exceptions. Real-world context, slang, and the general fluidity of language mean that “speaking” is far from a native process for computers. However, increasingly complex algorithms and large amounts of data have made it possible for NLP to accomplish extraordinary things.

Natural language processing examples include:Footnote 2

  • Email filters that automatically recognize spam based on written content.

  • Smart assistants, such as Siri and Alexa, that use voice recognition to accomplish spoken tasks.

  • Search results that return websites with content that matches the request.

  • Autocorrect and autocomplete functions that predict intended sentences.

Natural Language Processing | Introduction Image

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Why learn natural language processing 

Learning the basics of natural language processing can give you essential knowledge to better understand the growing world of machine learning, deep learning, and artificial intelligence. NLP is transforming the way businesses mine data, offering revolutionary insights into types of data that people have previously been unable to organize in a meaningful way. Humans communicate in unstructured ways (known as unstructured data). NLP work involves teaching computers to decipher that language similar to the way humans would. 

For example, we know that social media offers a wealth of information, but no human resources or customer service team can possibly analyze all of the data available. NLP allows machines to perform that sentiment analysis instead, illuminating key trends in customer journeys and freeing up human resources to make significant decisions. NLP can save time and money. Tasks that previously required humans can be performed by computers. NLP experts can help fill positions at companies hoping to make use of automated language solutions.Footnote 3

Natural language processing course curriculum

There is a wide range of options for how to learn natural language processing: introductory NLP courses, advanced courses that delve into artificial intelligence and deep learning, and NLP training programs that culminate in a professional certificate. An intro to NLP course might provide an overview of core natural language processing techniques and computational linguistics. It may cover topics like text processing, text mining, sentiment analysis, and topic modeling. Some of the specific tasks and processes that may be covered in an introductory NLP curriculum include:Footnote 4

  • Tokenization: breaking up a string of text into smaller parts called tokens (e.g., sentences or words) to make text easier to handle.

  • Part-of-speech tagging (PoS tagging): labeling tokens as verb, adverb, adjective, noun, etc. This helps infer the meaning of a word. 

  • Lemmatization and stemming: eliminating affixes and identifying the base form of words to make them easier to analyze.

  • Stop-word removal: removing frequently occurring words that don’t add any semantic value, such as I, they, have, like, yours, etc.

  • Bag of words: a representation model that concerns itself with the frequency of words in a selection of text, instead of word order or grammar.

More advanced courses, such as those on deep learning and artificial intelligence, may require certain prerequisites, like programming skills and knowledge of Python, as well as a background in classical machine learning.

Natural language processing jobs

Understanding the fundamental principles of natural language processing techniques may help you perform essential functions for your business. For example, speech recognition can assist a customer service branch, part of speech tagging helps build flexible databases, and accurate machine translation opens up possibilities for international expansion. 

Natural language understanding shifts the burden of gathering and understanding data from inconsistent human behavior to the massive processing capabilities of machines. Even if you are not a data science or computational linguistics professional, a solid understanding of NLP could be the gateway to a career in the new world of artificial intelligence.

Some job titles in this field include:

  • Natural language processing engineer/scientist

  • Applied scientist, NLP

  • Data engineer

  • Machine translation engineer

  • Data scientist

Depending on the particular job, it may require a bachelor’s degree or a master’s degree in computer science, data science, or a related subject. 

How to become a natural language processing engineer online

For those wondering how to become an NLP engineer, it will require a combination of education and experience. Many professionals in this field have a bachelor’s degree in computer or data science. Some employers may prefer to hire candidates with a master’s degree in engineering or a related field.Footnote 5

You will likely also need demonstrated experience in NLP, machine learning algorithms, and artificial intelligence. Some positions require a knowledge of Python and other programming languages. An online coding boot camp can be a good way to learn practical skills in a relatively short amount of time.