MSc in Artificial Intelligence
Julius-Maximilians-Universität Würzburg · Würzburg, Europe
Duration
18 mo
Tuition
No tuition fee
sourcedIntake
Summer semester
English
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Summer semester intake. Most universities admit on a rolling basis — we confirm the exact application deadline for your profile, free.
Course details verified 10 Sep 2026 — intakes, entry requirements and course facts · official source
Fee sourced Taken from the university's published fees page, not re-checked since — confirm it before you budget. See the university fees page.
About this programme
Our English-taught, consecutive, and research-oriented Master's in Artificial Intelligence equips you with in-depth knowledge of artificial intelligence applications and methods and teaches you how to conduct scientific research. It is specifically designed to foster a systematic understanding of artificial intelligence and the ability to apply it both practically and methodically. In this Master's programme, you will critically examine the key principles and methods of artificial intelligence, focusing on machine learning and mathematical foundations. You will also explore how such basic concepts can be transferred and adapted to relevant applications of artificial intelligence. This Master's programme opens up numerous career opportunities in AI, data science, cognitive computing, and many other fields. After graduating, you will be well prepared for developing AI systems in science, research, or industry. You will also be qualified for management roles to take responsibility for the development, integration, and safe operation of AI technologies. This Master's programme considers the implications and applications of artificial intelligence in practice. The knowledge and skills acquired are methodically and systematically applied in continuous scientific work. The ability to conduct independent scientific research includes, in particular, critically assessing existing solutions, transferring existing knowledge to new and unknown problems, and taking a structured approach to describing and solving problems based on a profound methodological understanding. The courses in the first semester cover key mathematical and methodological concepts in artificial intelligence, in particular, focusing on machine learning. Moreover, a "Scientific Seminar" module prepares for the scientific research students will carry out in subsequent semesters. The second semester emphasises specific applications and questions in AI, such as robotics, natural language processing, and computer vision, and it addresses ethical and legal implications. The competencies acquired in the second semester are consolidated and applied in teams during practical projects that are worth credits equivalent to two courses. Elective modules are also on offer in the first and third semesters for students to acquire specialised knowledge in their fields of interest. The Master's thesis in the third semester is for students to independently work on a topic of their choice, thereby applying scientific methods and the knowledge they have learned.
Intakes & deadlines
Summer semester
Dates confirmed for your profile · Open
Entry requirements
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English
E.G. TOEFL iBT Home Edition (before 2026): 83 Reading: 18 Listening: 17 Speaking: 20 Writing: 17 UNIcert® English: UNIcert® II IELTS Academic: 6
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Prerequisites
A completed university degree with 210 ECTS and an overall grade of 2.5 or above in computer science from a German university or an equivalent degree The less your Bachelor's degree is related to computer science, the more critical it is that you can credibly demonstrate how your studies have focussed on computer science / mathematics. We expect good to very good grades in all subjects relevant to the Master's degree programme, i.e. especially in mathematics and computer science (see below). Proof of this must be provided by submitting your Bachelor's degree certificate/transcript. Course certificates obtained outside of the Bachelor's programme cannot be considered proof. Letters of recommendation from teachers or school reports cannot be considered proof. The following content-oriented requirements must be met from your Bachelor’s: At least 20 ECTS should have been earned in mathematics from the Bachelor's preliminary studies, which provide sufficient knowledge in statistics/probability theory, (linear) algebra, and calculus. At least 15 ECTS in computer science should have been earned from the Bachelor's preliminary studies, which provide sufficient knowledge both in practical computer science (e.g. demonstrated by courses in databases, operating systems, software engineering, or distributed systems) and in theoretical computer science (e.g. shown by courses in algorithms and data structures, automata theory, complexity theory or logic). We strongly recommend ready-to-use programming skills (e.g. in Python), typically demonstrated by work samples from programming projects, internships, or laboratories. For this purpose, you can either upload your own source code to public repositories (Github, GitLab, bitbucket, etc) or, in the case of work experience, you can provide a qualified employer's reference stating your programming experience. We strongly recommend providing access to the applicants final thesis as proof of their scientific work (if possible, with the corresponding source code). These requirements must be understood as minimum requirements for successfully studying and completing the Master's programme.
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Documents
SOP, LOR & Resume — generate them free in 2 minutes.
This is an indicative early-career range for the whole Computer Science / IT field in Europe, from official graduate-outcome data — not a figure for this programme or university, and not a guarantee of what you will earn. What you actually earn depends on the role, employer, city and your visa.
Source: get in IT (Gehaltsstatistik Informatik 2026), 2026. Market job-board data — less official than a government survey; treat as indicative.
Rupee figure converted at the 18 Aug 2026 mid-market rate; your bank's rate will be worse and currencies move, so use it for planning, not as the amount you will receive.
Fees & scholarships
No tuition fee tuition (sourced). We confirm the exact costs and the scholarships you qualify for at Julius-Maximilians-Universität Würzburg — free, for your profile.
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MSc in Artificial Intelligence — FAQs
5 questions
Tuition is No tuition fee. Taken from the university's published fees page, not re-checked since — confirm it before you budget. We confirm the current fee and the scholarships you qualify for — free.
The main intake is Summer semester. Most universities admit on a rolling basis — we confirm the exact deadline for your profile, free.
A completed university degree with 210 ECTS and an overall grade of 2.5 or above in computer science from a German university or an equivalent degree The less your Bachelor's degree is related to computer science, the more critical it is that you can credibly demonstrate how your studies have focussed on computer science / mathematics. We expect good to very good grades in all subjects relevant to the Master's degree programme, i.e. especially in mathematics and computer science (see below). Proof of this must be provided by submitting your Bachelor's degree certificate/transcript. Course certificates obtained outside of the Bachelor's programme cannot be considered proof. Letters of recommendation from teachers or school reports cannot be considered proof. The following content-oriented requirements must be met from your Bachelor’s: At least 20 ECTS should have been earned in mathematics from the Bachelor's preliminary studies, which provide sufficient knowledge in statistics/probability theory, (linear) algebra, and calculus. At least 15 ECTS in computer science should have been earned from the Bachelor's preliminary studies, which provide sufficient knowledge both in practical computer science (e.g. demonstrated by courses in databases, operating systems, software engineering, or distributed systems) and in theoretical computer science (e.g. shown by courses in algorithms and data structures, automata theory, complexity theory or logic). We strongly recommend ready-to-use programming skills (e.g. in Python), typically demonstrated by work samples from programming projects, internships, or laboratories. For this purpose, you can either upload your own source code to public repositories (Github, GitLab, bitbucket, etc) or, in the case of work experience, you can provide a qualified employer's reference stating your programming experience. We strongly recommend providing access to the applicants final thesis as proof of their scientific work (if possible, with the corresponding source code). These requirements must be understood as minimum requirements for successfully studying and completing the Master's programme. English: E.G. TOEFL iBT Home Edition (before 2026): 83 Reading: 18 Listening: 17 Speaking: 20 Writing: 17 UNIcert® English: UNIcert® II IELTS Academic: 6.
The programme runs about 18 months full-time.
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