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CourseraArtificial IntelligenceFree courseCertificate

Natural Language Processing

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.

Created by: Anna Potapenko

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Overall Score : 88 / 100

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Course Description

This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few. Upon completing, you will be able to recognize NLP tasks in your day-to-day work, propose approaches, and judge what techniques are likely to work well. The final project is devoted to one of the most hot topics in today's NLP. You will build your own conversational chat-bot that will assist with search on StackOverflow website. The project will be based on practical assignments of the course, that will give you hands-on experience with such tasks as text classification, named entities recognition, and duplicates detection. Throughout the lectures, we will aim at finding a balance between traditional and deep learning techniques in NLP and cover them in parallel. For example, we will discuss word alignment models in machine translation and see how similar it is to attention mechanism in encoder-decoder neural networks. Core techniques are not treated as black boxes. On the contrary, you will get in-depth understanding of what's happening inside. To succeed in that, we expect your familiarity with the basics of linear algebra and probability theory, machine learning setup, and deep neural networks. Some materials are based on one-month-old papers and introduce you to the very state-of-the-art in NLP research.Do you have technical problems? Write to us: coursera@hse.ru

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Instructor Details

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Anna Potapenko graduated from Moscow State University with majors in Computer Science and Machine Learning. Now she is doing her PhD in natural language processing, particularly interested in learning semantic representations of words and documents. Anna was also working at Yandex and twice interning in Google, where she conducted research on deep neural networks and reinforcement learning for dialogue systems.

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Reviews

4.4

110 reviews in total

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By Ernst O on 4-Nov-19

Course has a high pace, and exposes students to many state-of-the-art as well as classic topics. Only topic missing are the recent BERT/ELMO models. This should be included. The lectures are good, but often cover too much ground to be understood fully, without further reading. Nice assignments. All in all worth it!

By Dmitry N on 30-Oct-19

Naaah, OK 5 out of 5. You, guys, are OK. Teaching stuff is great. And you are actually giving theoretical background, as Andrew Ng does. He might just have a bit more examples. But, I think, it was your first shot. And next course done by you, guys, for instance about GANS, will have a lot of examples. Thanks again.And looking good, you both.

By Timothy G on 14-Oct-19

This class of NLP came in handy for my current position. I recommend this class to others that real want to learn NLP.

By 刘禹杰 on 13-Oct-19

The quality of this course is good, but I still feel that the algorithm introduced is basic. It is better to combine the leading edge algorithms. Actually, I finished it very early, but I stuck in the fifth week of the dialogue robot job for a long time. I feel that this part of the time is not very worthwhile, because time is spent on the more cumbersome model deployment instead of focusing on Algorithm optimization, of course, model deployment is also very important, this is also a test for me, so I give 4 stars.

By Зубачев Д С on 2-Oct-19

It was a good course. All in one breath. I would like to have more practical tasks in which you need to write more code yourself, and not just fill in the missing cells. Of course, I am very grateful to Anna and Andrey for their work. Separately, we would like to note the penultimate task-the final project. It is complex and interesting. I believe that it would be correct to use the computing power of Azure instead of AWS.

By Bhavesh K on 26-Sep-19

This course was really helpful to me in understanding and being aware of the state of the art techniques in NLP.

By Joris D on 22-Sep-19

This is a very good course, brought with clarity and humour, and excellent quizzes and assignments to assess your understanding of the material. The big problem it has is the final project, which requires you to run a piece of software on an AWS free tier server. An impossibility, because the software requires more memory than Amazon offers in its free tier. Moreover, as it crashes every few hours, peer reviewers can find it not working and have to contact you to restart it. Constant monitoring for several days is required.

By Lefteris L on 22-Sep-19

This course offers a really good intro to all of the state of the art techniques used in NLP. Its course is structured by heavy impact papers from the literature and the instructors do a really good job in explaining. The quizzes are good and help you understand the material.If there is one thing I didn't like in this course, it was the programming assignments. Their structure was really big and aimed really long. Thus, I often felt that I didn't know what I was doing and for what reason. The assignments from Andrew Ng's Deep Learning's Specialization "Sequence Models" course were far better and helped me gain much intuition on how to code real tasks.

By Sifundo M on 20-Sep-19

This is a super excellent course, it does not only introduce you to natural language processing but takes all the way to be advance, in such a way that you can curate a bot straight from your mind, having no hardship thinking about the concept, i love the fact that this course does not spoon feed but gives enough information, to spark curiosity, in a way that you find yourself studying to master, through external sources, different views i loved it

By Loganathan S on 19-Sep-19

Very good and useful course.

By Neel K on 17-Sep-19

Course is well organized. Just some problems are related to assignments, There no exact guided steps for assignments and quiz. Lectures are more concerend about theory and less about pragmatic problems. Please make discussion forums active and more connected. Course does not have option to send message to anyone personally take help and advice which is something unrealistic.

By Pablo V I on 11-Sep-19

Very insightful course with challenging assignments. I highly recommend it!

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