The key to the fourth industrial revolution
Data-driven systems are at the centre of modern computer engineering and hold great promise for the future.
Data engineering is needed for solving challenging pattern recognition problems, such as intelligent search engines, self-driving cars, autonomous robots, or automatic car number plate recognition systems.
Extent of studies
Form of learning
Our major studies in Data Engineering and Machine Learning combine modern machine learning techniques with efficient implementation skills. Real-life deployment skills are not only about the mathematics of machine learning, but also require an understanding of databases, programming languages and even hardware design; all aiming at the efficient processing of huge data masses, with the best algorithms brought by modern machine learning.
More about the language of instruction
The official language of the programme is English, meaning that all the courses, exams and student services are arranged in English. Consequently, proficiency in both written and spoken English is an absolute prerequisite. Students are required to submit an approved certificate of their language proficiency when applying for admission. In addition, students are required to complete a course in the Finnish language. The course provides them with an introduction into everyday Finnish and Finnish culture.
The major in Data Engineering and Machine Learning contains courses from both machine learning and their efficient implementations. The machine learning courses cover both theory and practice and address a wide spectrum of machine learning techniques in classification, regression and unsupervised learning settings. We are committed to keeping the module up-to-date with the rapid advancements made in the field. We use modern toolsets, including the famous scikit-learn and Tensorflow libraries. On some courses, we also organise machine learning competitions where students solve research problems.
Tampere University offers students the opportunity for a broad, cross-disciplinary education. A rich variety of minor studies and supplementary courses are available as well as the opportunity to concentrate purely on major studies. In fact, each degree is a unique combination of studies that the individual student has found most interesting.
Structure of studies
The programme is comprised of 120 ECTS. Courses are worth 90 ECTS and the remaining 30 ECTS are awarded for successfully completing a master's thesis. Each ECTS is equal to an average workload of 27 hours, including lectures, exercises, assignments, independent study and an examination. The duration of the programme is two years. Students spend three semesters completing courses and one semester preparing the final project (master's thesis). They start their studies in late August, and the academic year ends in late May.
After completing the programme, you will be qualified to pursue a wide range of career opportunities in different fields of technology. The skills of data-driven problem solving are in high demand. This can be seen, for example, in surveys that demonstrate that data engineers are among the highest-paid of all professional programmers.
Graduated Masters of Science typically find employment in research, design, development, production and operating tasks, or commercial and administrative tasks relating to the field, without excluding abilities to work as a researcher, teacher or manager. Following the successful completion of the programme, our MSc graduates will be eligible to apply for admission to doctoral programmes in Finland or abroad.