Natural Language Processing with Attention Models from Coursera

In Course 4 of the Natural Language Processing Specialization, you will:

a) Translate complete English sentences into German using an encoder-decoder attention model,

b) Build a Transformer model to summarize text,

c) Use T5 and BERT models to perform question-answering, and

d) Build a chatbot using a Reformer model.

By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot!

Learners should have a working knowledge of machine learning, intermediate Python including experience with a deep learning framework (e.g., TensorFlow, Keras), as well as proficiency in calculus, linear algebra, and statistics. Please make sure that you’ve completed course 3 - Natural Language Processing with Sequence Models - before starting this course.

This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.

What's inside

Syllabus

Neural Machine Translation

Discover some of the shortcomings of a traditional seq2seq model and how to solve for them by adding an attention mechanism, then build a Neural Machine Translation model with Attention that translates English sentences into German.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops a foundation in natural language processing

Improves existing foundation in natural language processing

Taught by experts in the field

Provides practical experience through projects

Covers industry-standard tools and techniques

Requires prerequisite knowledge of certain modeling techniques

Coursework may require access to additional resources

Limited opportunities for direct feedback from instructors during lessons

Reviews summary

Advanced nlp with attention models: a practical deep dive

According to learners, this course provides a comprehensive and practical deep dive into advanced Natural Language Processing, focusing on cutting-edge attention models. Students particularly praise the coverage of architectures like Transformers, BERT, T5, and Reformer, and the opportunity to apply these through hands-on projects including Neural Machine Translation, text summarization, question answering, and chatbot development. While taught by highly experienced instructors, the course is described as having demanding prerequisites and a fast pace, making it best suited for learners with a solid background in deep learning.

Course moves quickly, requiring focused self-study and external resources.

"The pace is quite fast, but manageable if you dedicate enough time."

"While the topics are relevant, I found the explanations sometimes rushed, particularly for the Transformer."

"I had to consult external resources frequently to grasp the full concepts."

Taught by leading experts in NLP and deep learning.

"Łukasz Kaiser's insights on Transformers are unparalleled."

"The instructors are experts."

"It really helped solidify my understanding thanks to their clear explanations."

Features valuable projects on translation, summarization, and chatbots.

"The projects, especially the chatbot with Reformer, are very practical and challenging."

"The NMT project was a great hands-on experience."

"Great way to get hands-on with SOTA NLP models. The Question Answering module with BERT was particularly useful for my work."

Covers state-of-the-art NLP architectures like Transformers.

"Absolutely brilliant course! Łukasz Kaiser's insights on Transformers are unparalleled."

"Good content, covers state-of-the-art models like BERT and T5 well."

"The updated content, especially with the Reformer model, makes this course very current."

Requires strong background in deep learning, math, and Python.

"Prerequisites are no joke, make sure you're solid on deep learning before you start."

"I'm glad I completed Course 3 first, as it was definitely needed."

"The assignments are tough, perhaps too much for someone who just meets the minimum prerequisites."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Natural Language Processing with Attention Models with these activities:

Watch video tutorials on NLP

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Watching video tutorials on NLP will help you learn about the latest NLP techniques and how to apply them in practice.

Browse courses on NLP

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Find a video tutorial on NLP that you are interested in
Watch the tutorial and take notes

Review the basics of Python

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Reviewing the basics of Python will help you refresh your knowledge and ensure that you have a strong foundation for the course.

Browse courses on Python

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Go through a Python tutorial
Solve some basic Python coding challenges

Read 'Natural Language Processing with Python'

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Reading 'Natural Language Processing with Python' will help you learn about the foundations of NLP and how to apply them in practice.

View Natural Language Processing with Python:... on Amazon

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Read the book cover-to-cover
Do the exercises in the book

Five other activities

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Join a study group for the course

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Joining a study group for the course will help you learn from your peers and improve your understanding of the material.

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Find a study group for the course
Attend study group meetings regularly

Practice translating sentences using an encoder-decoder attention model

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Practicing translating sentences using an encoder-decoder attention model will help you develop the skills necessary to build your own neural machine translation model.

Browse courses on Neural Machine Translation

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Find a dataset of English-German sentence pairs
Build an encoder-decoder attention model in Python
Train the model on the dataset
Evaluate the model on a held-out set

Build a text summarization tool

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Building a text summarization tool will help you understand the concepts of text summarization and how to apply them in practice.

Browse courses on Text Summarization

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Choose a text summarization algorithm
Implement the algorithm in Python
Create a user interface for the tool
Test the tool on a variety of texts

Build a question-answering model

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Building a question-answering model will help you understand the concepts of question-answering and how to apply them in practice.

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Choose a question-answering dataset
Fine-tune a pre-trained language model on the dataset
Evaluate the model on a held-out set
Deploy the model as a web service

Contribute to an open-source NLP project

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Contributing to an open-source NLP project will help you learn about the latest NLP techniques and how to apply them in practice.

Browse courses on Open Source

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Find an open-source NLP project that you are interested in
Read the project documentation and contribute code
Submit a pull request to the project

Career center

Learners who complete Natural Language Processing with Attention Models will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Engineer

Natural Language Processing Engineers design and develop systems that enable computers to comprehend and interpret human language in a meaningful manner. This course can be particularly useful to those working in this role by bolstering their knowledge of attention models, which have advanced the field of NLP and improved the performance of NLP systems and applications.

See salaries and explore the career path for Natural Language Processing Engineer

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models and algorithms, which often include NLP models, to solve real world problems. Those in this role may find this course especially helpful for gaining in-depth knowledge about attention models and implementing them in NLP systems.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use their expertise in math, statistics, and computer science to extract knowledge from data, often using NLP techniques. This course may be especially valuable to Data Scientists looking to enhance their NLP skill set, particularly in the area of attention models.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, test, and maintain software systems. Those specializing in NLP may find this course particularly useful for acquiring knowledge about the latest NLP techniques and models, such as attention models, enabling them to build more effective and efficient NLP systems.

See salaries and explore the career path for Software Engineer

Research Scientist

Research Scientists conduct research and develop new theories and technologies. Those specializing in NLP may find this course especially helpful for gaining knowledge of cutting-edge NLP techniques, including attention models, which can inform their research.

See salaries and explore the career path for Research Scientist

Computational Linguist

Computational Linguists use their knowledge of linguistics and computer science to develop NLP systems. This course can be beneficial for those in this role by providing them with in-depth knowledge of attention models, a fundamental concept in modern NLP.

See salaries and explore the career path for Computational Linguist

Technical Writer

Technical Writers create and edit technical documentation, such as user manuals, white papers, and marketing materials. Those who specialize in NLP may find this course helpful for understanding the underlying concepts and techniques used in NLP, enabling them to write more accurate and informative documentation.

See salaries and explore the career path for Technical Writer

Product Manager

Product Managers oversee the development and launch of new products. Those working on NLP products may find this course useful for gaining a deeper understanding of NLP techniques, including attention models, which can help them make better decisions about product features and roadmaps.

See salaries and explore the career path for Product Manager

Business Analyst

Business Analysts analyze business needs and develop solutions using data and technology. Those specializing in NLP may find this course beneficial for gaining knowledge of NLP techniques, such as attention models, which can help them identify and solve business problems more effectively.

See salaries and explore the career path for Business Analyst

Project Manager

Project Managers plan, execute, and close projects. Those managing NLP projects may find this course helpful for gaining knowledge of NLP techniques, such as attention models, which can enable them to better understand project requirements and manage project risks.

See salaries and explore the career path for Project Manager

Data Architect

Data Architects design and build data architectures for organizations. Those specializing in NLP may find this course beneficial for gaining knowledge of NLP techniques, including attention models, which can help them design and build data architectures that support NLP applications.

See salaries and explore the career path for Data Architect

Information Security Analyst

Information Security Analysts protect organizations from cyber threats. Those specializing in NLP may find this course useful for gaining knowledge of NLP techniques, such as attention models, which can help them develop more effective security solutions.

See salaries and explore the career path for Information Security Analyst

IT Consultant

IT Consultants advise organizations on how to use technology to meet their business needs. Those specializing in NLP may find this course beneficial for gaining knowledge of NLP techniques, such as attention models, which can help them provide better advice to their clients.

See salaries and explore the career path for IT Consultant

UX Designer

UX Designers design user interfaces for websites and applications. Those specializing in NLP may find this course helpful for gaining knowledge of NLP techniques, such as attention models, which can help them design more user-friendly and efficient interfaces for NLP applications.

See salaries and explore the career path for UX Designer

Marketing Manager

Marketing Managers plan and execute marketing campaigns. Those specializing in NLP may find this course useful for gaining knowledge of NLP techniques, such as attention models, which can help them develop more effective marketing campaigns.

See salaries and explore the career path for Marketing Manager