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).
Syllabus 7
Introduction to the basics of Machine Translation 55 minutes
Language 3.5 hours
Evaluation 5 hours
Statistical Machine Translation 7 hours
Neural Network Models 3.5 hours
NMT 4 hours
More NMT 4 hours
Advantages and disadvantages
Advantages
Structured courses with graded quizzes, assignments and deadlines you can reset.
A shareable certificate from the university or company when you pay.
Financial aid is often approved for students in India (apply 15 days before you need it).
Self-paced: start any time.
A clear syllabus (7 parts) you can see before you start.
Disadvantages
Paid after a 7-day free trial (Coursera Plus or per course).
Some courses can be audited for free, but graded work and certificates need payment.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Taught by
Alexander WaibelProf. Dr., Interactive Systems Lab, Karlsruhe Institute of Technology
Jan NiehuesAssistant Professor, Faculty of Science and Engineering
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