B.Tech in Computer Science & Engineering (Data Science)

• Data Scientist
• Data Analyst
• Business Intelligence Analyst
• Machine Learning Engineer
• Data Engineer
• Big Data Engineer
• AI Engineer
• Business Analyst
• Data Visualization Specialist
• Cloud Data Engineer
• Statistical Analyst
• Research Associate
• Data Architect
• Analytics Consultant
• Higher Studies (M.Tech, MS, MBA, Ph.D.)

PO1: Engineering Knowledge

Apply engineering, mathematical, and statistical principles to solve data-driven computing problems.

PO2: Problem Analysis

Analyse complex datasets and identify meaningful patterns to support effective decision-making.

PO3: Design & Development

Develop data-driven applications and analytical solutions using modern computing techniques.

PO4: Investigation

Collect, process, analyse, and interpret data using scientific methods and analytical tools.

PO5: Modern Tool Usage

Utilise modern programming languages, data analytics platforms, cloud technologies, and machine learning frameworks effectively.

PO6: Professional Ethics

Apply ethical practices, data privacy principles, and professional responsibility while handling information and analytics.

PO7: Environment & Sustainability

Develop data-driven solutions that promote sustainable development and address societal challenges.

PO8: Individual & Team Work

Work efficiently as an individual and as a collaborative member or leader of multidisciplinary teams.

PO9: Communication

Communicate analytical findings and technical solutions effectively through reports, presentations, and visualizations.

PO10: Project Management

Apply project management, leadership, and entrepreneurial skills in data science and analytics projects.

PO11: Lifelong Learning

Continuously enhance knowledge and adapt to emerging technologies, analytical methods, and industry trends in data science.