Natural Language Processing with Deep Learning

XCS224N

Stanford School of Engineering

  • Fee:
    Fee may apply

Computer Science: Natural Language Processing with Deep Learning

Description

The field of natural language processing (NLP) is one of the most important and useful application areas of artificial intelligence. NLP is undergoing rapid evolution as new methods and toolsets converge with an ever-expanding availability of data. In this course you will explore the fundamental concepts of NLP and its role in current and emerging technologies. You will gain a thorough understanding of modern neural network algorithms for the processing of linguistic information. By mastering cutting-edge approaches, you will gain the skills to move from word representation and syntactic processing to designing and implementing complex deep learning models for question answering, machine translation, and other language understanding tasks.

What you will learn

  • Computational properties of natural languages
  • Neural network models for language understanding tasks
  • Word vectors, syntactic, and semantic processing
  • Coreference, question answering, and machine translation

Prerequisites

  • Proficiency in Python: All class assignments will be in Python (using NumPy and PyTorch). If you have extensive programming experience in a different language (C/C++/MATLAB/Java/JavaScript) we recommend you familiarize yourself with Python basics before the course begins.
  • College Calculus, Linear Algebra: You should be comfortable taking (multivariable) derivatives and understanding matrix/vector notation and operations.
  • Basic Probability and Statistics: You should know basics of probabilities, gaussian distributions, mean, and standard deviation.
  • Foundations of Machine Learning (recommended but not required): Knowledge of basic machine learning and/or deep learning is helpful, but not required.

Notes

This professional online course, based on the on-campus Stanford graduate course CS224N, features:

  • Classroom videos edited and segmented to focus on essential content
  • Coding assignments enhanced with added inline support and milestone code checks
  • Office hours and support from Stanford-affiliated Course Assistants
  • Cohort structure providing opportunities to network and collaborate with motivated learners from diverse locations and professional backgrounds 

Time Commitment

Expect to commit 8-12 hours/week for the duration of the 10-week program. 

Instructors

Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)

Abigail See
PhD Candidate, Computer Science
Head TA, CS224: Natural Language Processing with Deep Learning

Certificate

Upon completing this course, you will earn a Certificate of Achievement in Natural Language Processing with Deep Learning from the Stanford Center for Professional Development.

This is the first course in a series of Artificial Intelligence professional courses to be offered by the Stanford Center for Professional Development. You may earn a Professional Certificate in Artificial Intelligence by completing three courses in the program. The next course in the series is Natural Language Understanding, a project-focused course that is complementary to Natural Language Processing with Deep Learning. The Natural Language Understanding course will be offered Winter 2019-2020.

Application

Prior to enrolling in the course, you will be asked to complete a short application. The application allows you to share more about your interest in joining this cohort-based course, as well as verify that you meet the prerequisite requirements needed to make the most of the experience.

Questions?

Contact us at 650-204-3984
scpd-ai-proed@stanford.edu

003 Autumn 2019-20 Online

Enroll Now

Dates:December 2 - February 23, 2020
Days: Mon
Delivery Option:
Online
Fees:
Online Course $1,595.00 ?

Notes

 

****SEPTEMBER 2019 COHORT NOW FULL****

Cohort
This is a cohort-based program that will run from December 2, 2019 - February 23, 2020. The 10-week course will be spread over 12 weeks with a two week Stanford University winter break beginning close of business Friday, December 20 and returning on Monday, January 6, 2020. During this time all course materials and forums will be available for continued study, but no assignments will be due and student support will be unavailable. 

Online Program Materials 
Online program materials (slides etc.) are available for download from the course page. All materials are available for printing and review upon enrollment. Videos in the course are not downloadable however full length versions of the classroom videos are available on YouTube. 

Assignments
To successfully complete the program, participants will complete five assignments (mix of written questions and programming prompts). 

Course Evaluation
Participants are required to complete the program evaluation.

This course may not currently be available to learners in some states and territories.