MSc Artificial Intelligence

Opis i cele kształcenia

IU's MSc Artificial Intelligence develops the mathematical, algorithmic and systems competencies required of modern AI practitioners. You will progress from probability and classical learning through deep architectures, language models, vision and sequential decision-making, finishing with MLOps evaluation and governance. Lab work uses contemporary Python toolchains and structured peer review. The capstone produces a documented AI system with performance, safety and monitoring artefacts suitable for industrial or research scrutiny — not a demo notebook alone. MSc Artificial Intelligence is taught as one award, not a list of unrelated modules. The published length is 24 months, and the credit total is 36. Students move from Mathematics & Probability for AI through Mathematics & Probability for AI; Machine Learning Theory & Practice; Programming Intelligent Systems (Python); Data Engineering for ML Pipelines; Deep Learning & Representation Learning; Natural Language Processing & Large Language Models, and finish on MSc Artificial Intelligence Capstone Project. Each course has a question, a method, and a submission. In this field, students define a measurable question, fit a method that can be checked, and report where it fails. Reading is a dataset description, a methods note, and one published evaluation. The artefact a marker expects is a project note with the question, the method, the result, and the limitation. The award is built so that a graduate can do the following in practice: Design, train and evaluate supervised, unsupervised and deep learning models Build NLP and multimodal applications using modern transformer architectures Engineer reproducible ML pipelines with evaluation, monitoring and versioning Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.

Dyplom ukończenia studiów wydaje IU Międzynarodowy Uniwersytet Nauk Stosowanych z siedzibą w Warszawie. Kształcenie odbywa się w oparciu o polskie i europejskie standardy akademickie.

Struktura modułów i program nauczania

Program obejmuje 36 punktów ECTS zorganizowanych w moduły semestralne:

Forma kształcenia i zaliczenia

Perspektywy zawodowe absolwentów

• Machine Learning Engineer
• Applied AI Scientist
• NLP / Computer Vision Engineer
• MLOps Engineer
• AI Product Technical Lead

Kampus w Warszawie i zaplecze akademickie

Siedziba uczelni mieści się przy ul. Prostej 20 w Warszawie — w samym sercu stolicy Polski. Studenci stacjonarni korzystają z nowoczesnej infrastruktury dydaktycznej, a studenci online z pełnego wsparcia cyfrowego.

Główny gmach akademicki przy ul. Prostej 20 w Warszawie.

Dziedziniec uniwersytecki i przestrzenie seminaryjne.

Infrastruktura dydaktyczna i laboratoria wydziałowe.