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Machine Learning (S2-PRK-ML)

(in Polish: Machine Learning, stacjonarne, drugiego stopnia)
second cycle programme
full-time, 2-year studies
Language: English

Field: Science and natural sciences

Discipline: Computer science

Language of instruction: English

Professional degree you will be awarded after completing studies : Magister (MSc)

Where and when your classes will take place:

Place: Classes are held at the Ochota Campus, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, 2 Banacha Street.

Time: Classes are held from Monday to Friday between 8:30 am and 8:00 pm.

What kind of knowledge, skills and competencies you will acquire at this field of studies

Studying Machine Learning, you will gain solid mathematical and computer science foundations to efficiently design, train and implement machine learning models.

We will provide you with knowledge on:

  • mathematical models behind machine learning,
  • classical supervised and unsupervised learning methods as well as deep learning techniques,
  • large-scale distributed computing systems needed to train machine learning models,
  • machine learning techniques used in visual recognition, natural language processing, robotics and reinforcement learning,
  • ways to explain how artificial intelligence models work.

Studying Machine Learning will give you skills in:

  • programming in Python using ML libraries, e.g. TensorFlow, PyTorch, scikit-learn,
  • implementing and training ML and AI models on real-world datasets,
  • creating ML processing pipelines and deploying ML models in production environments,
  • optimizing code and models for performance and efficiency

In addition, we will prepare you for the changing needs of the environment by developing your social competences in:

  • critical and analytical thinking - the ability to assess the quality of models and select appropriate algorithms,
  • solving problems using ML algorithms in real-world applications,
  • teamwork
  • communicating results - presenting analysis and recommendations in a way that can be understood by a wide audience,
  • the need for continuous improvement - ML is a fast-paced and dynamic field that requires constant learning of new technologies and methods.

Studying ML will provide you with not only theoretical knowledge, but also practical skills that are valued in the technology industry.

Where you can find a job after completing studies

With a degree in Machine Learning, you can find work in a wide range of industries, as machine learning is widely used in data analysis, automation and artificial intelligence. Common career paths include positions such as ML Engineer, Data Scientist, AI Researcher or ML Software Engineer. While tech companies such as Google, Meta, Microsoft and OpenAI are heavily recruiting ML specialists, the financial, medical, e-commerce or industrial sectors are also increasingly deploying AI models to optimize processes. You can find jobs in large corporations, start-ups, as well as in academic or research environments.

Are there different specialties and specializations at the field of studies

We do not offer any specialties or specializations in the Machine Learning field of study.

What will you learn during the studies

Mathematical foundations are a key part of the ML degree programme, as they pave the way to development of models and algorithms in the field of machine learning. We develop competence in fundamental mathematical skills, providing proficiency in advanced statistical methods and neural network architectures. Mathematical analysis supports the understanding of data and the interpretability of models, which is important for the ethical implementation of artificial intelligence.

During ML studies you will explore advanced neural networks, learn how to train, optimize and solve typical problems. You will get to know how to control intelligent systems combining decision-making algorithms and machine learning in robotics. You will master image analysis and natural language processing techniques. You will understand how reinforcement learning can be applied to robotics, games and recommender systems.

We also offer activities to develop practical skills in machine learning. You will learn how to communicate effectively in teams and manage projects. During internships you will gain experience in companies, working on real projects and networking with experts. You will learn how to design algorithms for large datasets and how to use modern computational tools. Team projects will help you improve your collaborative and problem-solving skills. And during the MSc seminar you will deepen your knowledge in your chosen area before defending your thesis.

Will you pursue internship during the studies

After the first year of the Machine Learning major, you need to complete an internship, preferably during your summer break (July, August). The internship lasts for one month and should cover a total of 160 hours. Internships take place in companies dealing with machine learning applications. Instead of the internship, you may complete two or three several-day study visits in research groups working in fields related to machine learning.

Is it possible to study one/several semesters at other university

Yes, you can take part in the “MOST” or “ERASMUS+” programmes. The University of Warsaw participates in both programmes.

Where you can find more information on the study programme

You can find more information about Machine Learning studies in the Guide for students of Machine Learning at the Faculty of Mathematics, Informatics and Mechanics and on the website describing admissions to fields of study run by the Faculty of Mathematics, Informatics and Mechanics.

ECTS Coordinators:

Qualification awarded:

Second cycle degree - magister - in Machine Learning

Access to further studies:

doctoral school, non-degree postgraduate education

Learning outcomes

The graduate has achieved the learning outcomes defined for the second-cycle degree programme in Machine Learning in Annex to Resolution No. 38 of the Senate of the University of Warsaw of 17 March 2021 on Machine Learning programme (UW Monitor 2021, No. 75).

On completing this curriculum the student:
• is ready to realize social obligations, inspire and organize activities for the benefit of social environment;
• has based in theory and well organized knowledge of fundamental techniques of machine learning and methodology of constructions and research in this field;
• knows high-performance data processing techniques used in machine learning;
• has based in theory and well organized knowledge of problems of robot control, in particular of motion kinematics, movement planning and orientation in space;
• has based in theory and well organized knowledge of problems of image classification and object detection;
• knows methodologies, topics, techniques and tools in natural language processing;
• has in-depth understanding of the branches of mathematics necessary to study machine learning (probability theory, statistics, multivariable calculus, and linear algebra);
• is able to implement own algorithms and use existing libraries with reinforcement learning procedures;
• is able to process big data sets;
• is able to apply methods developed to study structures used in machine learning as well as to use them in the analysis of domain data.

Admission procedures:

Visit the following page for details on admission procedures: https://irk.uw.edu.pl/