Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The ‘Natural Language Processing’ online certification course is provided for the eligible students to equip themselves with the advanced skills of NLP for everyday tasks, suggest outlooks, and identify the optimum techniques. This online free course is provided by Coursera online education platform and the curriculum is developed by the HSE University. The course duration is designed to be completed in thirty-two hours and the students are allowed to work with flexible deadlines.
The course instructors for this online training are academic and industrial professionals Anna Potapenko(Researcher), Alexey Zobnin(Associate Professor), Anna Kozlova(Team Lead), Sergey Yudin(Analyst-Developer), etc. This course is part of the Advanced Machine Learning Specialization and enables participants to learn using course content provided with subtitles in Arabic, French, Portuguese, Italian, Vietnamese, Korean, German, Russian, English, Spanish, and other practical learning methodologies.
The ‘Natural Language Processing’ online training program helps students receive a course certificate that is shareable online after finishing the course study, assessments, and tests.
The Highlights
- Online mode
- Free training
- 32 hours course
- Financial aid
- Adjustable deadlines
- Course certificate
- Self-Paced learning
- Faculty from HSE University
- Subtitles
Programme Offerings
- videos
- Readings
- Practice Exercises
- Case Studies
- quizzes
- Graded Assignments
- Feedback
- tests
- Certificate
- Financial support
- Free registration
- Projects
- Independent Learning
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | HSE University |
The ‘Natural Language Processing’ certification fee is paid to get the certificate and the other certification benefits. Students can pay using the EMI options or can choose the audit mode for free training.
Natural Language Processing fee structure
Audit Mode | No |
One month(more than 20 hours/week) | ₹3,657 |
Three months(20 hours /week) | ₹7,314 |
Six months(10 hours/ week) | ₹10,972 |
Eligibility Criteria
The students interested in applying for the ‘Natural Language Processing’ certification by Coursera are expected to have prior knowledge of linear algebra, probability theories, machine learning concepts, and deep neural networks.
Certificate qualifying details:
The candidates of the ‘Natural Language Processing’ certification course by Coursera can get their course completion certificates after completing the course of study, graded assessments, tests, and projects.
What you will learn
The ‘Natural Language Processing’ certification syllabus enables the learners of this program to get familiar with the following aspects,
- The comparison, and study of traditional and deep learning strategies of NLP.
- Alignment models in machine translation and understanding its similarity with the attention mechanism in encoder-decoder neural networks.
- Classification of texts, identification of entities with names, and recognition of duplicates.
- Sentiment analysis, dialogue state tracking, and summarization.
Who it is for
The ‘Natural Language Processing’ online certification program is enabled for the students, individuals, and industry professionals who wish to improve their skills and knowledge with the advanced level concepts of natural language processing(NLP) to relate to real-life situations.
Admission Details
The students who wish to join the ‘Natural Language Processing’ online classes can join through the link on the course page,
Step1: Go to the course page on the Coursera website using the link below,
https://www.coursera.org/learn/language-processing
Step 2: Find the ‘Enroll For Free’ link.
Step 3: Click on the link and select the preferred mode of study.
Step 4: Make the course fee payment.
Step 5: Join the course.
Application Details
The applicants of the ‘Natural Language Processing’ online training course can register for the course with their name, email address, and the password for the course account or can sign in using their Google, Facebook, or Apple IDs.
The Syllabus
Videos
- About the University
- About this course
- Welcome video
- Main approaches in NLP
- A brief overview of the next weeks
- [Optional] Linguistic knowledge in NLP
- Text preprocessing
- Feature extraction from text
- Linear models for sentiment analysis
- Hashing trick in spam filtering
- Neural networks for words
- Neural networks for characters
Readings
- About University
- Rules on the academic integrity in the course
- Prerequisites check-list
- Hardware for the course
- Getting started with practical assignments
Practice exercises
- Classical text mining
- Simple neural networks for text
Videos
- Count! N-gram language models
- Perplexity: is our model surprised with a real text?
- Smoothing: what if we see new n-grams?
- Hidden Markov Models
- Viterbi algorithm: what are the most probable tags?
- MEMMs, CRFs, and other sequential models for Named Entity Recognition
- Neural Language Models
- Whether you need to predict the next word or a label - LSTM is here to help!
Readings
- Perplexity computation
- Probabilities of tag sequences in HMMs
Practice exercises
- Language modeling
- Sequence tagging with probabilistic models
Videos
- Distributional semantics: bee and honey vs. bee and bumblebee
- Explicit and implicit matrix factorization
- Word2vec and doc2vec (and how to evaluate them)
- Word analogies without magic: king – man + woman != queen
- Why words? From character to sentence embeddings
- Topic modeling: a way to navigate through text collections
- How to train PLSA?
- The zoo of topic models
Practice exercises
- Word and sentence embeddings
- Topic Models
Videos
- Introduction to Machine Translation
- Noisy channel: said in English, received in French
- Word Alignment Models
- encoder-decoder architecture
- Attention mechanism
- How to deal with a vocabulary?
- How to implement a conversational chatbot?
- Sequence to sequence learning: one-size fits all?
- Get to the point! Summarization with pointer-generator networks
Practice exercises
- Introduction to machine translation
- Encoder-decoder architectures
- Summarization and simplification
Videos
- Task-oriented dialog systems
- Intent classifier and slot tagger (NLU)
- Adding context to NLU
- Adding lexicon to NLU
- State tracking in DM
- Policy optimization in DM
- Final remark
Readings
- Instructions for Telegram bot hosted on AWS [Optional]
- Papers mentioned in week 5
- Keep up-to-date with NLP research
Practice exercise
Task-oriented dialog systems
Instructors
HSE University Frequently Asked Questions (FAQ's)
The course is for thirty-two hours.
The course is provided by Coursera with HSE University.
Yes, you can learn for free in the audit mode without access to the certificate and the graded assessments.
You can start the course at your preferred time and learn at your pace.
The certificate is given by HSE University.