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⇱ Natural Language Processing on Google Cloud | Coursera

Natural Language Processing on Google Cloud

Natural Language Processing on Google Cloud

23,318 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.4

540 reviews

Advanced level
Designed for those already in the industry
Flexible schedule
9 hours to complete
Learn at your own pace
78%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.4

540 reviews

Advanced level
Designed for those already in the industry
Flexible schedule
9 hours to complete
Learn at your own pace
78%
Most learners liked this course

Build your subject-matter expertise

This course is part of the Advanced Machine Learning on Google Cloud Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 7 modules in this course

This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

- Recognize the NLP products and the solutions on Google Cloud. - Create an end-to-end NLP workflow by using AutoML with Vertex AI. - Build different NLP models including DNN, RNN, LSTM, and GRU by using TensorFlow. - Recognize advanced NLP models such as encoder-decoder, attention mechanism, transformers, and BERT. - Understand transfer learning and apply pre-trained models to solve NLP problems. Prerequisites: Basic SQL, familiarity with Python and TensorFlow

This module addresses the reasons to learn NLP from Google and provides an overview of the course structure and goals.

What's included

2 videos1 reading

2 videos•Total 8 minutes
  • Meet the author•1 minute
  • Course introduction•7 minutes
1 reading•Total 10 minutes
  • Reading list•10 minutes

This module introduces the NLP architecture on Google Cloud. It explores the NLP history, the NLP APIs such as the Dialogflow API, and the NLP solutions such as Contact Center AI and Document AI.

What's included

7 videos1 reading1 assignment

7 videos•Total 34 minutes
  • Introduction•1 minute
  • What is NLP?•5 minutes
  • NLP history•3 minutes
  • NLP architecture•3 minutes
  • NLP APIs•10 minutes
  • NLP solutions•8 minutes
  • Summary•3 minutes
1 reading•Total 10 minutes
  • Reading list•10 minutes
1 assignment•Total 8 minutes
  • Quiz•8 minutes

This module explores AutoML and custom training, which are the two options to develop an NLP project with Vertex AI. Additionally, the module introduces an end-to-end NLP workflow and provides a hands-on lab to apply the workflow to solve a task of text classification with AutoML.

What's included

7 videos1 reading1 assignment

7 videos•Total 21 minutes
  • Introduction•1 minute
  • NLP options•3 minutes
  • Vertex AI•5 minutes
  • NLP with AutoML•4 minutes
  • NLP with custom training•2 minutes
  • NLP end-to-end workflow•4 minutes
  • Summary•2 minutes
1 reading•Total 10 minutes
  • Reading list•10 minutes
1 assignment•Total 6 minutes
  • Quiz•6 minutes

This module describes the process to prepare text data in NLP and introduces the major categories of text representation techniques.

What's included

8 videos1 reading1 assignment1 app item1 plugin

8 videos•Total 36 minutes
  • Introduction•2 minutes
  • Tokenization•6 minutes
  • One-hot encoding and bag-of-words•7 minutes
  • Word embeddings•4 minutes
  • Word2vec•9 minutes
  • Transfer learning and reusable embeddings•3 minutes
  • Lab introduction: Reusable Embeddings•1 minute
  • Summary•3 minutes
1 reading•Total 10 minutes
  • Reading list•10 minutes
1 assignment•Total 8 minutes
  • Quiz•8 minutes
1 app item•Total 60 minutes
  • Lab: Reusable Embeddings•60 minutes
1 plugin•Total 15 minutes
  • Accessing and completing labs•15 minutes

This module describes different NLP models including ANN, DNN, RNN, LSTM, and GRU. It also introduces the benefits and disadvantages of each model.

What's included

9 videos1 reading1 assignment1 app item

9 videos•Total 48 minutes
  • Introduction•2 minutes
  • ANN•11 minutes
  • TensorFlow•6 minutes
  • DNN•7 minutes
  • RNN•6 minutes
  • LSTM•8 minutes
  • GRU•2 minutes
  • Lab introduction: Text Classification with Keras•2 minutes
  • Summary•3 minutes
1 reading•Total 10 minutes
  • Reading list•10 minutes
1 assignment•Total 6 minutes
  • Quiz•6 minutes
1 app item•Total 120 minutes
  • Lab: Text Classification with Keras•120 minutes

This module introduces the state-of-the-art technologies and models in NLP: encoder-decoder, attention mechanism, transformers, BERT, and large language models.

What's included

8 videos1 reading1 assignment1 app item

8 videos•Total 31 minutes
  • Introduction•1 minute
  • Encoder-decoder architecture•3 minutes
  • Attention mechanism•3 minutes
  • Transformer•6 minutes
  • BERT•5 minutes
  • Large language models•8 minutes
  • Lab introduction: Text Translation using Encoder-decoder Architecture•0 minutes
  • Summary•3 minutes
1 reading•Total 10 minutes
  • Reading list•10 minutes
1 assignment•Total 6 minutes
  • Quiz•6 minutes
1 app item•Total 60 minutes
  • Lab: Text Translation using Encoder-decoder Architecture•60 minutes

This module reviews the topics covered in the course and provides additional resources for further learning.

What's included

1 video

1 video•Total 9 minutes
  • Course Summary•9 minutes

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Instructor

Instructor ratings
4.6 (29 ratings)
Google Cloud
2,244 Courses•4,416,115 learners

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Learner reviews

  • 5 stars

    64.25%

  • 4 stars

    22.40%

  • 3 stars

    7.40%

  • 2 stars

    2.59%

  • 1 star

    3.33%

Showing 3 of 540

MM
·

Reviewed on Jul 18, 2020

Everything was fine except the solution videos are old, that why you should update with update code.

AS
·

Reviewed on Aug 16, 2019

I like it because it is very relevant to my work. The dialogflow part is a bit weak. I am not sure if it is the product or the course.

HK
·

Reviewed on Nov 30, 2018

Very informative, very much useful to my ongoing work on NLP.

Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,