| Possess advanced theoretical and practical knowledge in mathematics, statistics, and probability necessary to analyze and model data science problems. | 3 | 2 | 1 | 3 | 1 | 2 | 3 | 3 | 1 | 1 |
| Effectively use modern programming languages and fundamental data structures to carry out data collection, data processing, and algorithm development processes. | 1 | 3 | 1 | 2 | 2 | 2 | 3 | 3 | 1 | 1 |
| Generate analytical solutions by examining complex and large datasets through visualization, exploratory data analysis, and statistical inference methods. | 2 | 2 | 1 | 3 | 1 | 1 | 2 | 2 | 1 | 1 |
| Take responsibility in interdisciplinary teams and communicate findings effectively in written and oral English at academic and professional levels. | 2 | 1 | 1 | 2 | 3 | 3 | 2 | 2 | 1 | 1 |
| Possess theoretical and practical mastery in designing, training, and optimizing machine learning and deep learning algorithms. | 3 | 3 | 2 | 3 | 2 | 2 | 3 | 3 | 1 | 2 |
| Manage end-to-end data engineering processes using big data ecosystems, database management systems, and cloud computing infrastructures. | 3 | 3 | 2 | 2 | 2 | 2 | 3 | 3 | 1 | 3 |
| Comprehend the global and societal impacts of computing and technology applications; possess the awareness to act in accordance with data privacy, intellectual property, and professional ethical standards. | 3 | 3 | 2 | 2 | 2 | 2 | 3 | 3 | 1 | 3 |
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