M.Sc in Data Science

01

Computational and Statistical Knowledge: Apply core and advanced knowledge of data science, including statistical modeling, algorithms, data structures, and machine learning techniques, for problem-solving and analysis.

02

Problem Analysis: Identify, model, and analyze complex real-world problems using statistical and computational approaches grounded in scientific and domain-specific knowledge.

03

Design/Development of Solutions: Design and develop scalable and efficient data-driven solutions using appropriate data science tools and technologies, considering ethical, social, and environmental aspects.

04

Conduct Investigations of Complex Problems: Employ data-driven experimentation, simulation, and model validation techniques to investigate and interpret complex datasets.

05

Modern Tool Usage: Utilize current data science platforms, programming environments, and cloud-based tools to preprocess data, build models, and deploy solutions effectively.

06

Professional Ethics: Uphold ethical practices in data collection, analysis, sharing, and storage, maintaining integrity, fairness, and respect for privacy and regulations.

07

Life-long Learning: Engage in continuous professional development and learning to keep abreast of emerging tools, techniques, and theoretical advancements in data science.

08

Project Management and Finance: Demonstrate project planning, budgeting, and execution skills, and lead or contribute effectively within interdisciplinary teams.

09

Communication Efficacy: Communicate technical findings clearly and effectively through reports, presentations, data visualizations, and stakeholder interactions.

10

Societal and Environmental Concern: Assess the broader societal, legal, and environmental implications of data science applications, promoting sustainable and inclusive innovation.

11

Individual and Team Work: Exhibit the ability to work independently and collaboratively in diverse teams, demonstrating leadership, accountability, and adaptability.

12

Innovation and Entrepreneurship: Leverage data science skills to innovate, identify startup opportunities, and drive technological advancement and economic growth.

01

Be equipped to pursue advanced research in core areas of Data Science and interdisciplinary domains at nationally and internationally reputed institutions.

02

Excel in professional roles across academia, research labs, corporates, and government sectors, and contribute to technological and societal growth through entrepreneurial ventures.

03

Be engaged with cutting-edge roles in data analytics, machine learning, artificial intelligence, business intelligence, and other data-driven domains across global industries, consultancy services, and higher education.