About this Course

138,887 recent views

Learner Career Outcomes

38%

started a new career after completing these courses

42%

got a tangible career benefit from this course

43%

got a pay increase or promotion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 34 hours to complete

Suggested: 5 weeks of study, 4-5 hours per week...

English

Subtitles: English

Skills you will gain

ChatterbotTensorflowDeep LearningNatural Language Processing

Learner Career Outcomes

38%

started a new career after completing these courses

42%

got a tangible career benefit from this course

43%

got a pay increase or promotion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 34 hours to complete

Suggested: 5 weeks of study, 4-5 hours per week...

English

Subtitles: English

Syllabus - What you will learn from this course

Content RatingThumbs Up88%(3,508 ratings)Info
Week
1

Week 1

5 hours to complete

Intro and text classification

5 hours to complete
11 videos (Total 114 min), 3 readings, 3 quizzes
11 videos
Welcome video5m
Main approaches in NLP7m
Brief overview of the next weeks7m
[Optional] Linguistic knowledge in NLP10m
Text preprocessing14m
Feature extraction from text14m
Linear models for sentiment analysis10m
Hashing trick in spam filtering17m
Neural networks for words14m
Neural networks for characters8m
3 readings
Prerequisites check-list2m
Hardware for the course5m
Getting started with practical assignments20m
2 practice exercises
Classical text mining10m
Simple neural networks for text10m
Week
2

Week 2

5 hours to complete

Language modeling and sequence tagging

5 hours to complete
8 videos (Total 84 min), 2 readings, 3 quizzes
8 videos
Perplexity: is our model surprised with a real text?8m
Smoothing: what if we see new n-grams?7m
Hidden Markov Models13m
Viterbi algorithm: what are the most probable tags?11m
MEMMs, CRFs and other sequential models for Named Entity Recognition11m
Neural Language Models9m
Whether you need to predict a next word or a label - LSTM is here to help!11m
2 readings
Perplexity computation10m
Probabilities of tag sequences in HMMs20m
2 practice exercises
Language modeling15m
Sequence tagging with probabilistic models20m
Week
3

Week 3

5 hours to complete

Vector Space Models of Semantics

5 hours to complete
8 videos (Total 83 min)
8 videos
Explicit and implicit matrix factorization13m
Word2vec and doc2vec (and how to evaluate them)10m
Word analogies without magic: king – man + woman != queen11m
Why words? From character to sentence embeddings11m
Topic modeling: a way to navigate through text collections7m
How to train PLSA?6m
The zoo of topic models13m
2 practice exercises
Word and sentence embeddings15m
Topic Models10m
Week
4

Week 4

5 hours to complete

Sequence to sequence tasks

5 hours to complete
9 videos (Total 98 min)
9 videos
Noisy channel: said in English, received in French6m
Word Alignment Models12m
Encoder-decoder architecture6m
Attention mechanism9m
How to deal with a vocabulary?12m
How to implement a conversational chat-bot?11m
Sequence to sequence learning: one-size fits all?10m
Get to the point! Summarization with pointer-generator networks12m
3 practice exercises
Introduction to machine translation10m
Encoder-decoder architectures20m
Summarization and simplification15m
4.6
131 ReviewsChevron Right

Top reviews from Natural Language Processing

By GYMar 24th 2018

Great thanks to this amazing course! I learned a lot on state-to-art natural language processing techniques! Really like your awesome programming assignments! See you HSE guys in next class!

By YYJan 2nd 2019

I like this course very much. It is a good introduction for NLP. But if you want to know more about the NLP, you need to search and read a lot of posts during the learning process.

Instructors

Instructor rating4.38/5 (18 Ratings)Info
Image of instructor, Anna Potapenko

Anna Potapenko 

Researcher
HSE Faculty of Computer Science
49,720 Learners
1 Course
Image of instructor, Alexey Zobnin

Alexey Zobnin 

Accosiate professor
HSE Faculty of Computer Science
52,059 Learners
3 Courses
Image of instructor, Anna Kozlova

Anna Kozlova 

Team Lead
Yandex
49,720 Learners
1 Course
Image of instructor, Sergey Yudin

Sergey Yudin 

Analyst-developer
Yandex
49,720 Learners
1 Course
Image of instructor, Andrei Zimovnov

Andrei Zimovnov 

Senior Lecturer
HSE Faculty of Computer Science
89,306 Learners
2 Courses

Offered by

National Research University Higher School of Economics logo

National Research University Higher School of Economics

About the Advanced Machine Learning Specialization

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....
Advanced Machine 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.