The Master of Science in Machine Learning degree aims to provide theoretical and practical foundations that enable its graduates to be at the forefront of progress in machine learning and related disciplines. Machine learning is a rapidly expanding field with many applications in diverse areas, such as intelligent systems, perception, robotics, finance, information retrieval, bioinformatics, healthcare, weather prediction among others. In addition to established employers in these industries, a large number of startups have also entered the market seeking to hire machine learning scientists. Besides careers in industry, this program will prepare students for the pursuit of doctoral degrees and careers in research.

The program prepares students to:

• Establish a career as a machine learning scientist in either industry or academia.

• Develop a deep understanding of machine learning theory and become familiar with the most important machine learning paradigms.

• Select and apply appropriate machine learning models on real-world applications in various areas of science and engineering.

Program Outcomes

Upon completion of the program, students will be able to:

• Understand the theory underlying machine learning algorithms.

• Use machine learning to make decisions and predictions.

• Select appropriate statistical and predictive methodologies.

• Build statistical learning models and understand their strengths and limitations.

• Provide appropriate interpretation of classification or regression results.