Vision

• The data revolution has created novel challenges and unprecedented opportunities. The vision of the Department of Data Science is to create a first-class academic department that trains the next generation of students as data scientists who will solve these grand challenges and innovate through world-class research to take advantage of these opportunities.

Mission

• Educate students in a field that has ushered in a once-in-a-generation revolution, comparable to the industrial revolution and the original computing revolution.
• Provide an environment for leading edge research that has a strong and rapid impact on the economy and that reestablishes RGMCET as a world leader in technological advancement.
• Create a source of scholarship on the many technical, ethical, and privacy issues that ubiquitous data creation is constantly confronting us with.
• Establish a center of technology knowledge and a "go to organization" to service data creators, providers, managers, curators, and users of the State and the Nation.

Program Specific Outcomes (PSO's)

1. Ability to apply mathematical and statistical models, computing theory, the principles of optimization, as well as languages and algorithms, and to appropriately formulate and use data analysis.
2. Ability to apply the principles and techniques of database design, and implementation to enhance data collection capabilities and decision-support systems.
3. Ability to invent and use appropriate models of data analysis, assess the quality of input, derive insight from results and investigate potential issues. Also to organize big data sets into meaningful structures, incorporating data profiling and quality standards.

Objectives of the Program : After the completion of the degree, students would -

• Be prepared with a varied range of expertise in different aspects of data science such as data collection, visualization, processing and modeling of large data sets
• Acquire good understanding of both the theory and application of applied statistics mathematics and computer science based existing data science models to analyse huge data sets originating from diversified application areas.
• Be able to create models using the knowledge acquired from the program to solve future challenges and real-world problems requiring large scale data analysis.
• Be better trained professionals to cater the growing demand for data scientists and engineers in industry.

Program Outcomes (PO's) - Engineering Graduates will be able to:

1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.