Data science is an interdisciplinary field of scientific methods, processes and systems for understanding the modern-age data sources, modeling the data behavior, extracting the business insight from that data, predicting future behavior and delivering useful data-driven business applications. In 2013, IBM estimated that two and a half million terabytes of data are created every day. Some of the sources, generating the data are:

• Individuals (through social networks and smartphones for the reflection of society)
• Machines (through real-time, network-connected sensors – Internet of things)
• Business and commerce (e.g. transaction records and financial data)
• Education (e.g. academics, literature, research)
• Medical / Healthcare (personal health records, health insurance)
• Justice (crime statistics for a city for the sake of efficient resource deployment)
• Transportation (Vehicle, pedestrians, trains, airlines, movement data)

The challenge is to make sense of this ever-increasing source of data for the use and benefit of society. A lot many companies and higher education institutions are already planning and implementing the programs to cater to this data tsunami. Data science has emerged as an interdisciplinary paradigm that draws upon the traditionally distinct areas of computer science, applied mathematics and statistics, applications from natural and social science, engineering, and business for developing solutions for gathering, cleaning, archiving, analyzing and visualizing data for the purposes of making informed decisions.

The Bachelors of Science in Data Science (BS-DS) program aims to develop core competencies in various areas of data science like understanding data products, data extraction, data cleaning, data modeling, classification, clustering, predictions, etc. Students will have the opportunity of learning the technical aspects of data science by understanding the trends in the current data products and preparing for the required data analysis skillset for the upcoming information processing systems. To cater to a wide range of professional and academic interests, students have the option of selecting their course work according to their specific needs. Riphah Institute of Systems Engineering (RISE) is currently offering MS (Information Security) and MS (Data Science) programs that are expected to not only complement each other but also will open new opportunities for coping with the challenges of the near future.

Graduate Attributes (Program Learning Outcomes)

GA-1   Academic Education: Completion of an accredited program of study designed to prepare graduates as computing professionals.

GA-2   Knowledge for Solving Computing Problems: Apply knowledge of computing fundamentals, knowledge of a computing specialization, and mathematics, science, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements.

GA-3   Problem Analysis: Identify and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.

GA-4   Design/Development of Solutions: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs.

GA-5   Modern Tool Usage: select, or adapt and then apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations

GA-6   Individual and Teamwork: Function effectively as an individual and as a member or leader of a team in multidisciplinary settings.

GA-7   Communication: Communicate effectively with the computing community about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.

GA-8   Computing Professionalism and Society: Understand and assess societal, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice

GA-9   Ethics: Understand and commit to professional ethics, responsibilities, and norms of professional computing practice.

GA-10   Life-long Learning: Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.

Program Objectives (Program Educational Objectives)

• Fundamental Knowledge: Be successful in developing data driven solutions for complex industrial problems using modern tools and technologies.
• Professionalism: Be successful in diverse computing related professions by mastering technical skills along positive attitude by working in team with empathy and professionalism.
• Team and Leadership: Accomplish tasks effectively as individuals, team members, and leaders in their profession.
• Ethical Responsibilities: Adopt universal Islamic ethical values within a given professional environment and society.
• Continuous Professional Development: Engage in life-long learning and professional development.