Machine Translation
- Offered byCoursera
- Public/Government Institute
Machine Translation at Coursera Overview
Duration | 27 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
Machine Translation at Coursera Highlights
- Earn a shareable certificate upon completion.
- Flexible deadlines according to your schedule.
Machine Translation at Coursera Course details
- Welcome to the CLICS-Machine Translation MOOC
- This MOOC explains the basic principles of machine translation. Machine translation is the task of translating from one natural language to another natural language. Therefore, these algorithms can help people communicate in different languages. Such algorithms are used in common applications, from Google Translate to apps on your mobile device.
- After taking this course you will be able to understand the main difficulties of translating natural languages and the principles of different machine translation approaches. A main focus of the course will be the current state-of-the-art neural machine translation technology which uses deep learning methods to model the translation process. You will be able to decide which concepts fit your machine translation application best.
- This course is taught by Prof. Dr. Alexander Waibel (http://isl.anthropomatik.kit.edu/english/21_74.php) and Assistant Professor Dr. Jan Niehus (https://www.maastrichtuniversity.nl/jan.niehues).
Machine Translation at Coursera Curriculum
Introduction to the basics of Machine Translation
Introduction
History
Approaches
Applications
Overview
Additional materials
Introduction
History
Approaches
Applications
Introduction
Language
Language
Difficulties
Approaches to MT
Data
Additional materials
Additional materials
Additional materials
Additional materials
Language
Difficulties
Approaches
Data
Evaluation
Evaluation
Human Evaluation
BLEU
MT Metrics
Additional materials
Additional materials
Additional materials
Additional materials
Evaluation
Human Evaluation
BLEU
Machine Translation Metrics
Statistical Machine Translation
Word-based Statistical Machine Translation
Language Model
From Noisy channel model to Log-linear Model
Phrase based Machine Translation
Advanced SMT
Additional materials
Additional materials
Additional materials
Additional materials
Word-based Statistical Machine Translation
Language Model
From Noisy-channel model to Log-linear model
Advanced SMT
Neural Network Models
Introduction to Neutral Networks
Feed Foward Neural Network Language Model
Reccurent Neural Network Language Model
Neural Translation Model
Additional materials
Additional materials
Additional materials
Additional materials
Introduction to Neural Networks
Feed Forward Neural Network Language Model
Recurrent Neural Network Language Model
Neural Translation Model
NMT
Encoder Decoder
NMT Training
NMT Decoding
Attention Based NMT
Combination
Additional materials
Additional materials
Additional materials
Additional materials
Encoder-Decoder
NMT-Training
NMT Decoding
Attention based NMT
Combination
More NMT
Vocabulary
Monolingual Data
Multilingual Machine Translation
Architectures
Additional materials
Additional materials
Additional materials
Additional materials
Vocabulary
Monolingual Data
Multilingual
NMT - Architectures
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