Deep Learning for Natural Language Processing

Software > Computer Software > Educational Software University of Colorado Boulder

Course Overview

Deep learning has revolutionized the field of natural language processing and led to many state-of-the-art results. This course introduces students to neural network models and training algorithms frequently used in natural language processing. At the end of this course, learners will be able to explain and implement feedforward networks, recurrent neural networks, and transformers. They will also have an understanding of transfer learning and the inner workings of large language models. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Course FAQs

What are the prerequisites for 'Deep Learning for Natural Language Processing'?

Prerequisites for this continuing education class are set by University of Colorado Boulder. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.

Will I receive a certificate for this CE class?

Yes, upon successful completion, University of Colorado Boulder typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.

How long does this online course take to complete?

Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.