Overview
Key Features
During the second cycle studies, the primary emphasis is on learning creative problem solving, the ability to build generalizations and pose questions. Graduates of the second-cycle studies become proficient not only in the use of selected information processing technologies in the field of machine learning, but they are also able to use the acquired knowledge and skills in applications unrelated to the studied discipline, for example in interdisciplinary research teams. As a result, graduates are prepared for careers that require significant knowledge of machine learning to cope with contemporary challenges facing computer solutions. At the same time, students are included in the research conducted at the university, which prepares the graduates to conduct scientific research activities and undertake doctoral studies.
Studies in machine learning allow future graduates to acquire advanced knowledge and skills in techniques used in machine learning, including: statistical methods for machine learning, deep neural networks, reinforcement learning, and explanation of results obtained from machine learning procedures. They also become familiar with basic machine learning application domains such as visual recognition, autonomous device control, and natural language processing. As a result, graduates of the Machine Learning programme offered at the University of Warsaw are prepared to design, oversee, and critically analyze IT projects with significant machine learning components, to serve in expert roles in machine learning, and to be leaders beyond the university world. Graduates of the Master of Science in Machine Learning have the knowledge and skills to pursue a third-cycle degree in computer science.Programme Structure
Courses include:
- Ideas and informatics
- Statistical machine learning
- Deep neural networks
- Robot control
- Visual recognition
- Natural language processing
Key information
Duration
- Full-time
- 24 months
Start dates & application deadlines
- Starting
- Apply before
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Language
Credits
Delivered
Campus Location
- Warsaw, Poland
Disciplines
Machine LearningWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Other requirements
General requirements
- Minimum percentage of points needed to be qualified: 45%
- Admission to the second-cycle studies programme may be granted to candidates holding a bachelor's degree, master's degree, engineer's degree or an equivalent degree in any field of study.
- The qualification is based on the results of the entrance exam.
- Form of examination: written, in English. The exam will cover topics related to mathematical analysis, linear algebra, foundations of mathematics, discrete mathematics, probability theory and statistics, numerical methods, algorithms and data structures, concurrent programming and the theory of languages and automata.
- The scope of the examination problems will be published at the IRK system.
- On the basis of the results of the written qualification examination, the Admission Committee creates a ranking list of candidates, taking the number of points from the examination expressed as a percentage of each candidate's score.
Student Insurance via Studyportals Partner
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items like Additional medical costs, Repatriation, Liability etc. Make sure your student insurance covers your needs.
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Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree -
EU/EEA Applies to you
Applies to youEU/EEA NationalsFree
Additional Details
Free of charge.
Living costs
Warsaw
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Machine Learning.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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