About this Course
612,928 recent views

Course 5 of 5 in the

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 17 hours to complete

Suggested: 11 hours/week...

English

Subtitles: English, Korean, Spanish, Chinese (Simplified)
User
Learners taking this Course are
  • Data Scientists
  • Machine Learning Engineers
  • Biostatisticians
  • Scientists
  • Researchers

Skills you will gain

Recurrent Neural NetworkArtificial Neural NetworkDeep LearningLong Short-Term Memory (ISTM)
User
Learners taking this Course are
  • Data Scientists
  • Machine Learning Engineers
  • Biostatisticians
  • Scientists
  • Researchers

Course 5 of 5 in the

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 17 hours to complete

Suggested: 11 hours/week...

English

Subtitles: English, Korean, Spanish, Chinese (Simplified)

Syllabus - What you will learn from this course

Week
1
6 hours to complete

Recurrent Neural Networks

12 videos (Total 112 min), 2 readings, 4 quizzes
12 videos
Notation9m
Recurrent Neural Network Model16m
Backpropagation through time6m
Different types of RNNs9m
Language model and sequence generation12m
Sampling novel sequences8m
Vanishing gradients with RNNs6m
Gated Recurrent Unit (GRU)17m
Long Short Term Memory (LSTM)9m
Bidirectional RNN8m
Deep RNNs5m
2 readings
Gated Recurrent Unit (GRU) *CORRECTION*1m
Long Short Term Memory (LSTM) *CORRECTION*1m
1 practice exercise
Recurrent Neural Networks20m
Week
2
4 hours to complete

Natural Language Processing & Word Embeddings

10 videos (Total 102 min), 1 reading, 3 quizzes
10 videos
Using word embeddings9m
Properties of word embeddings11m
Embedding matrix5m
Learning word embeddings10m
Word2Vec12m
Negative Sampling11m
GloVe word vectors11m
Sentiment Classification7m
Debiasing word embeddings11m
1 reading
GloVe word vectors *CORRECTION*1m
1 practice exercise
Natural Language Processing & Word Embeddings20m
Week
3
5 hours to complete

Sequence models & Attention mechanism

11 videos (Total 103 min), 1 reading, 3 quizzes
11 videos
Picking the most likely sentence8m
Beam Search11m
Refinements to Beam Search11m
Error analysis in beam search9m
Bleu Score (optional)16m
Attention Model Intuition9m
Attention Model12m
Speech recognition8m
Trigger Word Detection5m
Conclusion and thank you2m
1 reading
Bleu Score *CORRECTION*1m
1 practice exercise
Sequence models & Attention mechanism20m
4.8
1824 ReviewsChevron Right

39%

started a new career after completing these courses

39%

got a tangible career benefit from this course

12%

got a pay increase or promotion

Top reviews from Sequence Models

By AMJul 1st 2019

The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.

By JYOct 30th 2018

The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.

Instructors

Avatar

Andrew Ng

CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
Avatar

Head Teaching Assistant - Kian Katanforoosh

Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
Avatar

Teaching Assistant - Younes Bensouda Mourri

Mathematical & Computational Sciences, Stanford University, deeplearning.ai
Computer Science

About deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

About the Deep Learning Specialization

If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI....
Deep Learning

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.