BS Data Science
Program Educational Objectives (PEOs)
The following program educational objectives (PEOs) are expected to be demonstrated by Data Science graduates within 4 years of their graduation. Data science professionals will:
PEO 1: Emphasizes the application of computing and data science fundamentals in professional roles, preparing graduates for real-world challenges.
PEO 2: Highlights the importance of ethical practices in data handling, reflecting a growing societal concern for data privacy and protection.
PEO 3: Stresses the need for effective verbal and written communication, crucial for collaboration and dissemination of information in professional settings.
PEO 4: Encourages graduates to take on leadership roles, fostering teamwork and entrepreneurial spirit, vital in today’s collaborative work environments.
PEO 5: Promotes a culture of lifelong learning and exploration of new fields, essential in the rapidly evolving data science landscape.
Program Learning Outcomes (PLOs)
Here are the Program Learning Outcomes (PLOs) for the BS Data Science program, based on the provided details:
PLO 1: Problem Investigation
Focuses on a systematic approach to addressing complex data science problems, enhancing critical thinking and analytical skills.
Focuses on a systematic approach to addressing complex data science problems, enhancing critical thinking and analytical skills.
PLO 2: Mathematics and Science Application
Ensures graduates can leverage foundational knowledge to tackle intricate issues in data science effectively.
Ensures graduates can leverage foundational knowledge to tackle intricate issues in data science effectively.
PLO 3: Issue Identification and Analysis
Trains graduates to critically assess and formulate responses to complex data challenges using established principles.
Trains graduates to critically assess and formulate responses to complex data challenges using established principles.
PLO 4: Designing Solutions
Encourages innovative design thinking while considering various implications, fostering a holistic approach to problem-solving.
Encourages innovative design thinking while considering various implications, fostering a holistic approach to problem-solving.
PLO 5: Modern Tool Usage
Prepares graduates to effectively employ modern data science tools, equipping them to handle practical tasks and understand their limitations.
Prepares graduates to effectively employ modern data science tools, equipping them to handle practical tasks and understand their limitations.
PLO 6: Teamwork and Leadership
Promotes the ability to work in multidisciplinary teams, reflecting the collaborative nature of data science projects.
Promotes the ability to work in multidisciplinary teams, reflecting the collaborative nature of data science projects.
PLO 7: Effective Communication
Highlights the necessity of clear communication in conveying technical information, an essential skill in any professional context.
Highlights the necessity of clear communication in conveying technical information, an essential skill in any professional context.
PLO 8: Context-Aware Reasoning
Encourages graduates to consider broader societal issues when applying data science practices, promoting responsible decision-making.
Encourages graduates to consider broader societal issues when applying data science practices, promoting responsible decision-making.
PLO 9: Professional Ethics
Instills a commitment to ethical standards in professional practice, crucial for building trust in data-driven decision-making.
Instills a commitment to ethical standards in professional practice, crucial for building trust in data-driven decision-making.
PLO 10: Lifelong Learning
Reinforces the importance of adapting to new technologies and innovations, ensuring graduates remain relevant in their field.
Reinforces the importance of adapting to new technologies and innovations, ensuring graduates remain relevant in their field.
PLO 11: Societal and Environmental Impact
Demonstrate an entrepreneurial mindset with the capability to initiate successful startups that create social and economic impact.
Demonstrate an entrepreneurial mindset with the capability to initiate successful startups that create social and economic impact.
PLO 12: Project Management
Focuses on the integration of data science principles with management skills to effectively lead and manage projects in diverse contexts.
Focuses on the integration of data science principles with management skills to effectively lead and manage projects in diverse contexts.
PEOs-PLOs Mapping
| PLOs | PEOs | ||||
|---|---|---|---|---|---|
| PEO 1 | PEO 2 | PEO 3 | PEO 4 | PEO 5 | |
| PLO-01: Problem Investigation | ✔ | ||||
| PLO-02: Mathematics and Science Application | ✔ | ||||
| PLO-03: Issue Identification and Analysis | ✔ | ||||
| PLO-04: Designing Solutions | ✔ | ||||
| PLO-05: Modern Tool Usage | ✔ | ✔ | |||
| PLO-06: Teamwork and Leadership | ✔ | ||||
| PLO-07: Effective Communication | ✔ | ✔ | |||
| PLO-08: Context-Aware Reasoning | ✔ | ||||
| PLO-09: Professional Ethics | ✔ | ||||
| PLO-10: Lifelong Learning | |||||
| PLO-11: Societal and Environmental Impact | ✔ | ||||
| PLO-12: Project Management | ✔ | ✔ | |||
