CHARLES UNIVERSITY · CZECHIA
Statistical Machine Translation
Master's · Taught in en · UCAS NPFL087
At a glance
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Duration
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IELTS
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Tuition / yr
en
Language
Master's
Level
- 5E-credits
- Summer semesterSemester
- Project-based learningLearning Style
- State-of-the-art systemsFocus
- Inverted Classroom/Flipped Class modeTeaching Method
This course delves into the field of machine translation (MT), exploring its current scope and various state-of-the-art systems. You will gain a deep understanding of phrase-based MT, surface-syntactic MT, and deep-syntactic MT. The curriculum also covers essential prerequisites and related areas such as extracting translation equivalents from parallel texts, word alignment techniques, MT evaluation, and system combination methods. The course aims to provide a unified perspective on MT as a statistical search process, enhanced by practical project work. Emerging approaches like neural networks will also be introduced.
Curriculum
The course covers a range of topics in machine translation, with lectures typically held weekly. The learning format is an 'inverted classroom' where students watch pre-recorded lectures beforehand and engage in discussions and Q&A during live sessions.
- Week 0
- Class Overview and Project Suggestions0
- Week 1
- Metrics of MT Quality1
- Week 2
- Overview of Approaches to MT: SMT, PBMT, NMT2
- Week 3
- Introduction to Neural Machine Translation (NMT)3
- Week 4
- Alignment4
- Week 5 (No Lecture before Easter)
- Week 6
- Phrase-Based Machine Translation5
- Week 7
- Morphology in MT6
- Week 8
- Syntax in SMT7
- Week 9 (April 20, 2023 - Note: Year mismatch)
- Transformer; Syntax in NMT8
Careers
This course provides a strong foundation in machine translation, preparing students for roles in areas like natural language processing, computational linguistics, and AI development. Graduates are equipped to work on improving translation systems, developing new MT technologies, and researching advancements in the field.
- Machine Translation Engineer
- Computational Linguist
- NLP Researcher
- Data Scientist (NLP focus)
- AI Developer
Frequently asked questions
- What are the tuition fees for the Statistical Machine Translation programme?
- For students enrolling from the 2024/2025 academic year onwards, the tuition fee is 420,000 CZK per year. This fee covers tuition only and does not include living expenses or other study costs. An exchange rate of 1 EUR = 25 CZK is provided for reference.
- What is the duration of the Statistical Machine Translation master's programme?
- The programme duration is not explicitly stated in the provided information. However, tuition fees are listed for up to the 6th year of study, which may indicate a potential maximum duration.
- How is the Statistical Machine Translation course taught?
- The course uses an 'inverted classroom' or 'flipped classroom' model. Students watch pre-recorded lectures before class and then participate in live sessions for discussions and Q&A. Project-based learning is a key component.
- What are the career prospects after completing the Statistical Machine Translation programme?
- Graduates can pursue roles such as Machine Translation Engineer, Computational Linguist, NLP Researcher, Data Scientist with an NLP focus, or AI Developer. The course prepares students for careers in natural language processing and AI development.
- How can I apply for the Statistical Machine Translation programme?
- Detailed application steps for this specific course are limited. Prospective students should check the Charles University admissions portal for general procedures, review program eligibility, prepare required documents like transcripts and a statement of purpose, and submit their application online by the specified deadlines.
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Fees
Tuition (international)420,000 CZK (for students enrolled starting 2024/2025 or later, for 1st-6th year of study)
Tuition (home)420,000 CZK (for students enrolled starting 2024/2025 or later, for 1st-6th year of study)
LivingNot specified
Tuition fees are listed for various academic years, with the most recent being 420,000 CZK per year for students enrolled from the 2024/2025 academic year onwards. These fees do not cover living or other study costs. Exchange rate information provided: 1 EUR = 25 CZK.
How to apply
1. Check Eligibility and RequirementsReview the program details and ensure you meet the academic and any language proficiency requirements. For Master's level programs, a relevant Bachelor's degree is typically required.
2. Prepare Application DocumentsGather necessary documents, which may include academic transcripts, degree certificates, letters of recommendation, and a statement of purpose. Specific requirements can vary by program.
3. Submit ApplicationComplete the online application form via the Charles University admissions portal. Pay attention to submission deadlines.
4. Application ReviewThe faculty will review your application. Some programs may require an entrance examination or interview.
5. Receive Offer of AdmissionSuccessful applicants will receive an offer of admission.
6. Accept Offer and EnrollAccept the offer and complete the enrollment process, including paying any required fees.
Scholarships
Computer Science Tuition Fee ScholarshipsVaries
PhD ScholarshipStarting at 10,500 CZK per month
Financial support programme for Mathematics PhD StudentsGuaranteed monthly income 20,000 CZK (tax exempt); typically around 25,000 CZK total monthly income.
Employment programme for Computer Science PhD StudentsMinimal monthly salary 20,000 CZK + 12,500 CZK tax-free monthly stipend. Typical median monthly increase from grant projects was 11,000 CZK in 2024/25.
Accreditation
Not specified
Frequently asked questions
What are the tuition fees for the Statistical Machine Translation programme?
+
For students enrolling from the 2024/2025 academic year onwards, the tuition fee is 420,000 CZK per year. This fee covers tuition only and does not include living expenses or other study costs. An exchange rate of 1 EUR = 25 CZK is provided for reference.
What is the duration of the Statistical Machine Translation master's programme?
+
The programme duration is not explicitly stated in the provided information. However, tuition fees are listed for up to the 6th year of study, which may indicate a potential maximum duration.
How is the Statistical Machine Translation course taught?
+
The course uses an 'inverted classroom' or 'flipped classroom' model. Students watch pre-recorded lectures before class and then participate in live sessions for discussions and Q&A. Project-based learning is a key component.
What are the career prospects after completing the Statistical Machine Translation programme?
+
Graduates can pursue roles such as Machine Translation Engineer, Computational Linguist, NLP Researcher, Data Scientist with an NLP focus, or AI Developer. The course prepares students for careers in natural language processing and AI development.
How can I apply for the Statistical Machine Translation programme?
+
Detailed application steps for this specific course are limited. Prospective students should check the Charles University admissions portal for general procedures, review program eligibility, prepare required documents like transcripts and a statement of purpose, and submit their application online by the specified deadlines.