Our Programmes

B. Sc. Computer Science with Data Science

Department Vision

  • The Department of B.Sc. (Data Science) aims to equip students with industry-relevant skills in data science, AI, and automation, fostering global competence.
  • It aims for recognition through innovation, excellence in education, and collaborative research.
  • The focus is on preparing graduates who are ready to contribute to societal needs and sustainable solutions.
  • The department aims to achieve excellence in data science education, research, and entrepreneurship, serving both industry and society.

Department Mission

  • Develop a state-of-the-art infrastructure to foster an industry-conducive environment for data-driven solutions.
  • Empower students with innovative cognitive solutions through data analytics skills and advancements in high-performance computing.
  • Foster entrepreneurial qualities and leadership in students, encouraging them to meet industry and community needs with ethical standards.
  • Encourage interdisciplinary research and collaboration with industry to solve complex, real-world problems.
  • Course Structure

Program Outcomes

  • Scientific knowledge:
    Apply your understanding of physics, math, and computing to solve challenging scientific problems.
  • Problem analysis:
    Apply first principles of mathematics, natural sciences, and applied sciences to identify, formulate, research, and analyse complex scientific problems in order to reach substantiated conclusions.
  • Design/development of solutions:
    In order to meet specified needs, design systems or processes that take public health and safety, as well as cultural, societal, and environmental factors, into appropriate account.
  • Perform inquiries into intricate issues:
    For the purpose of drawing reliable findings, apply research-based knowledge and techniques, such as experiment design, data analysis and interpretation, and information synthesis.
  • Utilising current computing and IT tools:
    Develop, pick, and apply suitable methods, resources, and tools, such as modelling and prediction, to intricate scientific tasks while being aware of their limitations.
  • The software developer and the community:
    Use reasoning based on contextual knowledge to evaluate concerns related to society, health, safety, law, and culture, as well as the ensuing obligations that are pertinent to professional activity.
  • Sustainability and the environment:
    Show that you are aware of the importance of sustainable development and that you comprehend how professional software engineering solutions affect society and the environment.
  • Ethics:
    Adhere to professional ethics, duties, and standards of scientific conduct. Apply ethical concepts.
  • Communication:
    Convey difficult information to the scientific community and the general public in an effective manner. This includes understanding and producing reports and documentation, designing presentations, and giving and receiving clear directions.
  • Project management:
    Exhibit comprehension of scientific and management ideas and apply them to one's own work, as a team member and leader, to oversee projects, and in contexts involving several disciplines.
  • Lifelong learning:
    Understand the importance of lifelong learning and possess the skills necessary to pursue it independently in the broadest context of technological change.

Program Specific Outcomes

  • Apply Data Science principles, including visualization, management, and security, to build intelligent predictive models for solving real-world problems.
  • Apply AI and Data Science skills in diverse fields like Healthcare, Education, Agriculture, Intelligent Transport, Environment, and Smart Systems to solve real-world problems.
  • Use analytic technologies to derive actionable foresight, insights, and hindsight from data for solving business and engineering challenges.
  • Leverage AI and Data Science techniques to predict future events in sectors like Healthcare, Education, Agriculture, Manufacturing, Automation, Robotics, and Transport.
  • Enhance critical thinking in emerging technologies such as Hybrid Mobile apps, cloud technology, and cyber-physical systems, applying mathematical models to research and solution development.
  • Use Business Analytics, Visualization, and Statistical Tools, gained through certifications, projects, internships, and lab exercises, to address critical issues.
  • Foster continuous learning and independent development to qualify for careers in AI and Data Science, adapting to the evolving technological landscape.
  • Learners will:
  • Acquire essential programming and technical skills to handle computational demands and perform data analysis effectively.
  • Develop strong critical thinking skills to analyze complex problems and formulate innovative solutions using data science methodologies.
  • Adapt to modern tools and techniques in data science to design and implement domain-based solutions in real-world scenarios.
  • Work effectively in diverse teams, making collaborative decisions and contributing to achieving project goals.
  • Communicate data science concepts clearly through written reports and presentations, catering to both technical and non-technical audiences.
  • Use advanced digital tools and programming languages for data analysis, modeling, and the creation of effective data-driven solutions.
  • Recognize and address ethical issues in data science projects, ensuring responsible practices and decisions.