| Title | Description |
|---|---|
| PEO 1 | Establish successful careers in data science, artificial intelligence, business analytics, research, and related domains by applying advanced analytical and computational skills. |
| PEO 2 | Pursue higher studies, research, innovation, and entrepreneurship in emerging areas of data science, machine learning, deep learning, and intelligent systems. |
| PEO 3 | Demonstrate professional ethics, leadership qualities, effective communication, teamwork, and lifelong learning while addressing societal and industrial challenges through data-driven solutions. |
| Title | Description |
|---|---|
| PSO 1 | Data Analytics and Intelligence Apply statistical modelling, machine learning, deep learning, and artificial intelligence techniques to extract knowledge and generate actionable insights from data. |
| PSO 2 | Data Engineering and Computing Design and implement scalable data pipelines, big data processing systems, cloud-based analytics solutions, and intelligent applications using modern technologies. |
| PSO 3 | Domain-Specific Data Science Applications Develop innovative data-driven solutions for diverse domains such as healthcare, finance, business, manufacturing, social media, agriculture, and scientific research while adhering to ethical and sustainable practices. |
| Title | Description |
|---|---|
| PO 1 | Data Science Knowledge Apply advanced concepts of statistics, mathematics, computer science, machine learning, artificial intelligence, and data analytics to solve real-world problems. |
| PO 2 | Problem Analysis Identify, formulate, analyse, and interpret complex data-driven problems using scientific and analytical approaches. |
| PO 3 | Data Management and Processing Acquire, clean, transform, integrate, and manage structured and unstructured data using modern data engineering techniques. |
| PO 4 | Analytics and Modelling Develop predictive, prescriptive, and descriptive models using statistical methods, machine learning, and deep learning algorithms. |
| PO 5 | Modern Tools Usage Utilize contemporary data science tools, programming languages, cloud platforms, big data frameworks, and visualization technologies effectively. |
| PO 6 | Research and Innovation Design and conduct research investigations, evaluate outcomes, and develop innovative solutions for emerging data science challenges. |
| PO 7 | Ethics and Responsible AI Apply ethical principles, data privacy regulations, fairness, transparency, and responsible AI practices in professional activities. |
| PO 8 | Communication Skills Communicate analytical findings effectively through reports, dashboards, visualizations, presentations, and technical documentation. |
| PO 9 | Individual and Team Work Function effectively as an individual, team member, or leader in multidisciplinary and collaborative environments. |
| PO 10 | Project Management and Entrepreneurship Apply project management principles, entrepreneurial thinking, and business analytics to create value-driven solutions. |
| PO 11 | Societal and Environmental Responsibility Evaluate the impact of data-driven decisions on society, sustainability, governance, and public welfare. |
| PO 12 | Life-Long Learning Engage in continuous learning and adapt to evolving technologies, methodologies, and professional practices in data science. |
