DSML Program Objectives and Student Outcomes

By the time of graduation, graduates of the program will have an ability to:

1. Ability to apply computing, mathematics, and machine learning to data science.
2. Ability to analyze datasets, identify patterns, and extract insights for problem-solving.
3. Ability to design, implement, and evaluate data models, machine learning algorithms, and systems.
4. Ability to communicate effectively with stakeholders using data and modeling to solve problems.
5. Understanding of ethical, legal, and social issues related to data and machine learning models.
6. Ability to communicate data insights to a variety of audiences and provide actionable recommendations.
7. Ability to assess the impact of data science solutions on individuals, organizations, and society.
8. Recognition of the need for ongoing professional development in machine learning.
9. Ability to use current techniques, tools, and skills for data analysis, visualization, and machine learning.
10. Ability to apply statistical, algorithmic, and machine learning theory in designing data-driven systems, considering trade-offs.
11. Ability to apply design principles in creating data pipelines, preprocessing systems, and machine learning models.