Skills you'll gain: Machine Learning, Natural Language Processing, Human Computer Interaction, User Experience, Artificial Neural Networks, Computer Graphics, Deep Learning, Interactive Design, Computer Programming, Computer Programming Tools, Other Programming Languages
Intermediate · Course · 1-3 Months
Skills you'll gain: Machine Learning, Business Analysis, Applied Machine Learning, Business Transformation, Data Analysis, Data Model, Deep Learning, Exploratory Data Analysis, Forecasting, Human Computer Interaction, Natural Language Processing, People Analysis, Probability & Statistics, Reinforcement Learning, Statistical Analysis, Artificial Neural Networks, Machine Learning Algorithms
Beginner · Course · 1-4 Weeks
Skills you'll gain: Machine Learning, Applied Machine Learning, Artificial Neural Networks, Machine Learning Algorithms, Machine Learning Software, Natural Language Processing, Statistical Machine Learning, Algebra, Computer Vision, Data Engineering, Data Science, Deep Learning, Econometrics, Mathematics, Python Programming, Tensorflow
Advanced · Course · 1-4 Weeks
Skills you'll gain: Machine Learning, Cloud Computing, IBM Cloud, Python Programming, Data Analysis, Computer Vision, Computer Programming, Computer Science, Data Structures, Programming Principles, Algebra, Applied Machine Learning, Computational Thinking, Data Science, Computer Graphics, Theoretical Computer Science, Computer Graphic Techniques, Deep Learning, Natural Language Processing, Statistical Programming, Algorithms, Artificial Neural Networks, Machine Learning Software, Basic Descriptive Statistics, Computational Logic, Design and Product, Exploratory Data Analysis, Human Computer Interaction, Interactive Design, Other Web Frameworks, Product Design, Web Development, Application Development, Cloud API, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Operating Systems, Software Engineering, Software Engineering Tools, Software Testing, Systems Design, Web Development Tools
Beginner · Professional Certificate · 3-6 Months
Beginner · Specialization · 3-6 Months
Natural language processing, or NLP, is the field of artificial intelligence (AI) focused on enabling computers to understand and use human language. By drawing on insights from linguistics and cutting edge computer science, NLP is playing an increasingly important role in helping computers understand people - and, conversely, in helping humans better navigate our increasingly digital world.
For example, NLP is essential to programming digital assistants that respond accurately to voice commands, such as Alexa or Google Home. It also enables the creation of chatbots capable of addressing common customer service inquiries. Beyond customer-facing tools, NLP is also used for sentiment analysis applications used by businesses to assess social media responses to their brand, or services capable of automatically creating clearly-written summaries of text or datasets.
Like other areas of AI and deep learning, NLP relies on machine learning (ML) algorithms organized in neural network architectures. Because neural networks mimic the structure of the human brain itself, these approaches are particularly well suited for natural language processing. And, as with other AI/ML applications, work in NLP is most commonly done in TensorFlow or Python programming.
Natural language processing is one of the trending job skills in Coursera's 2020 Global Skills Index (GSI). Download the 2020 edition of the GSI report.
It’s an exciting time to work in natural language processing, as more and more organizations are exploring ways to use chatbots, digital assistants, and other NLP applications. This trend has been further accelerated by the Covid-19 epidemic, as the transition away from physical help desks and customer service departments has led companies to try new modes of interacting with customers. Thus, a familiarity with NLP approaches can be useful to software developers, data scientists, and other professionals in tech.
Professionals wishing to leverage their expertise in natural language processing to develop new approaches in this field may pursue a master’s degree or even a doctorate in computer science. In NLP and other areas, computer research scientists are in high demand; according to the Bureau of Labor Statistics, they earn a median annual salary of $122,840 per year, and jobs in this field are expected to grow much faster than average over the next decade.
Certainly. Coursera offers a wealth of courses and Specializations in computer science, data science, and artificial intelligence, including courses specifically focused on NLP applications. These courses are offered by top-ranked institutions such as deeplearning.ai, the University of Michigan, and the National Research University Higher School of Economics. You can also learn about NLP with hands-on Guided Projects from Coursera, which help you build new skills with tutorials presented by experienced instructors.
The skills or experience you may need to have before starting to learn about natural language processing (NLP) can include understanding the basics of linguistics, programming, and statistical analysis. You may also want to have the ability to understand the basic concepts of artificial intelligence. Also, you may need to have some familiarity with the basics of linear algebra, probability theory, machine learning setup, and deep neural networks. The ability to understand linguistics means you may already know the meaning of semantics and symbolism in language. Having a basic understanding of programming and statistical analysis may be required because NLP is used to help humans interact with all kinds of computers and devices. In addition, you have experience in industries, such as medicine, law, or finance and banking, you may already have some skills needed to learn NLP because artificial intelligence, or the algorithms used to understand and manipulate human language, is already being used for tools such as medical records, legal documents, and financial insights.
The kind of person best suited to learn NLP is interested in language and words. People who like to understand the subtle and ambiguous ways that words and sentences convey meaning to a human enjoy learning about NLP. Someone interested in how devices use artificial intelligence to make decisions for humans may be well suited to learn NLP. A person who is comfortable living in the world of automated language and personal assistants (such as Siri and Alexa) may find learning NLP worthwhile too.
Learning NLP may be right for you if you're passionate about the future of artificial intelligence. NLP may be beneficial for you to learn if you plan to work as a software developer in the field of artificial intelligence that requires complex programming skills, applications, and systems such as machine translation of sentences and building chatbots, for example. NLP may be beneficial for you to learn if you need to understand algorithms, such as Naïve Bayes Classifier, which is a common classification algorithm that makes fast machine predictions. Studying NLP may also be right for you if you are a software developer who needs to understand how to build NLP systems using TensorFlow, a popular open-source framework for machine learning.