Learning Outcomes

Upon successful completion of the MSc in Interdisciplinary Data Science and Artificial Intelligence (MIDSAI) at NYU Abu Dhabi, students will have achieved the following program learning outcomes:

Specialized Knowledge

Articulate highly specialized knowledge of data science and artificial intelligence, at the interface between data science, artificial intelligence, and other domain science(s), including recent developments and emerging trends.

Advanced Problem-solving Skills

Demonstrate advanced skills that integrate knowledge in computing theory, languages, algorithms, mathematical and statistical models, and the principles of optimization to formulate and develop innovative solutions to academic/professional problems with intellectual independence.

Advanced Research Skills

Develop new skills and knowledge through undirected study, self-training, and bibliographic research, in order to design, create, and implement a research project.

Interdisciplinary Techniques and Perspectives

Apply advanced data analysis and computational modeling techniques to a variety of interdisciplinary problems. Students will learn to work effectively in interdisciplinary teams, leveraging diverse skills and perspectives to address complex data science challenges.

Effective Communication of Findings

Demonstrate the ability to effectively communicate data science findings to a variety of audiences, including domain experts and non-technical stakeholders.

Implications to Society

Understand and address the ethical, legal, and societal implications of data science and artificial intelligence, including issues of privacy, bias, and fairness.

Self-evaluation and Growth

Self-evaluate performance, learning needs, and professional knowledge in new and novel contexts related to data.