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All courses are taught in English. The master project is also written in English. To complete the programme 90 ECTS are required of which 70 ECTS is from course work and 20 ECTS from the Master Project. The master project is mandatory for all students. The courses are divided in: Preparatory, Core and Elective. Preparatory are advanced undergraduate courses which might be required to fill possible gaps necessary to follow the programme. Each Preparatory course is 5 ECTS which includes 2hrs/week lectures plus homework and/or lab assignments and a final exam and/or project. A maximum of 10 ECTS can be credited from preparatory courses. There are three Core courses which are mandatory for all students and account for total of 30 ECTS. The remaining required ECTS can be completed by taking Elective courses. Core and Elective courses are 10 ECTS each, and includes 4hrs/week lectures plus homework and/or lab assignments and a final exam and/or project.
Semester A (20-30 ECTS)
Preparatory Courses: Data Structures(5 ECTS), Numerical Algorithms(5 ECTS), Probability Theory(5 ECTS)
Core Courses: Mathematical & Computational Statistics (10 ECTS), Introduction to Data Science(10 ECTS)
Semester B (30 ECTS)
Core Courses: Introduction to Machine Learning(10 ECTS)
Two(2) elective courses with 10 ECTS/course
Semester C (30 – 40 ECTS)
Master Project(20 ECTS)
One-two (1-2) elective courses with 10 ECTS/course
Εθνικό Μετσόβιο Πολυτεχνείο: Επιστήμη Δεδομένων και Μηχανική Μάθηση (Data Science and Machine Learning)