Student Outcomes:

The students of BS Data Science program are expected to attain the following outcomes by the time of graduation.

1. SO1: Apply knowledge of computing fundamentals, mathematics, statistics, data science, and relevant domain knowledge to abstract, conceptualize, and solve data-driven computing problems.
2. SO2: Identify, formulate, research, and analyze complex data science problems using appropriate principles of mathematics, statistics, computing sciences, and relevant domain disciplines.
3. SO3: Design, develop, implement, and evaluate data-driven solutions, analytical models, and data science systems that meet specified needs while considering societal, cultural, environmental, and ethical requirements.
4. SO4: Select, adapt, and apply appropriate statistical methods, data analytics techniques, programming languages, computational resources, and modern data science tools while understanding their capabilities and limitations.
5. SO5: Function effectively as an individual and as a member or leader of diverse and multidisciplinary teams to accomplish data science projects and organizational objectives.
6. SO6: Communicate effectively with computing professionals, data science practitioners, and society through technical reports, data visualizations, documentation, presentations, and clear written and verbal communication.
7. SO7: Analyze and evaluate the societal, legal, economic, cultural, environmental, privacy, and security implications of data collection, analysis, storage, and use in local and global contexts.
8. SO8: Apply ethical principles, professional responsibilities, data privacy, security, fairness, transparency, and responsible data practices in the design and application of data science solutions.
9. SO9: Recognize the need for and demonstrate the ability to engage in independent and continuous learning to remain current with emerging data science methodologies, technologies, tools, and professional practices.
10. SO10: Conduct systematic data-driven research, experimentation, and critical evaluation to develop innovative solutions, generate meaningful insights, and contribute to the advancement of data science knowledge and practice.

The SOs provides graduates with the basis for attaining PEOs during their professional tenure. The broader defined PEOs were decomposed into more measurable and achievable SOs related to PEOs.

PEO-SO Mapping:

The student outcomes are mapped with the program educational objectives so that if we achieve the program learning outcomes, the program educational objectives would be considered to have been completed. The mapping of SOs with PEOs is mentioned in Table 5. Teaching different curriculum courses could achieve the program’s learning outcomes. As mentioned later, all these courses are related to the program learning outcome. Each course has its course learning outcome. Suppose the learning outcome of the course is achieved. In that case, the respective program learning outcome will be achieved, and ultimately, by attaining the program learning outcomes, we will accomplish the program’s educational objectives.