Overview of the Department of Computer Science, Information Technology, Data Science, Artificial Intelligence and Machine Learning

The Department of Computer Science, Information Technology, Data Science, Artificial Intelligence and Machine Learning provides quality education and practical training in emerging technologies. It equips students with skills in programming, software development, databases, networking, cloud computing, cybersecurity, data analytics, AI, and machine learning. Through projects, internships, workshops, hackathons, research, and industry collaborations, the Department fosters innovation, problem-solving skills, and career readiness for the IT industry, academia, research, and entrepreneurship.

The Computer Science and Information Technology streams build strong foundations in programming, algorithms, operating systems, computer networks, software engineering, web technologies, mobile application development, and database management. The Data Science stream emphasizes data collection, processing, visualization, statistical analysis, predictive modelling, and data-driven decision-making.

The Artificial Intelligence and Machine Learning areas focus on intelligent systems, machine learning algorithms, deep learning, natural language processing, computer vision, generative AI, and real-world AI applications. Students gain hands-on experience with modern programming languages, development platforms, data science tools, and AI/ML frameworks.

Vision

To become a centre of excellence in Computer Science, Information Technology, Data Science, Artificial Intelligence and Machine Learning, producing skilled, innovative, ethical, and socially responsible professionals.

Mission

• To provide quality education in computing and emerging technologies.
• To develop strong programming, analytical, and problem-solving skills.
• To promote research, innovation, entrepreneurship, and interdisciplinary learning.
• To provide hands-on exposure through laboratories, projects, internships, and industry interaction.
• To prepare students for successful careers and higher education in technology-related fields.
• To encourage the ethical and responsible use of technology for societal development.

B.Sc. Computer Science

B.Sc. Information Technology / B.Sc. Data Science / B.Sc. Artificial Intelligence & Machine Learning

Programme Outcomes (POs)

• PO 1 Communication Skill: Mandatory language courses facilitate to become proficient in communication, culturally aware, and more employable in both Indian and global contexts. Improve presentations skill, debates, and professional communication.
• PO 2 Disciplinary Knowledge: Learn in-depth complex scientific concepts, demonstrate their ability to explain and apply their knowledge. Consistent in learning by earning extra credits in specialized courses within the science domain and enhance disciplinary knowledge.
• PO 3 Critical thinking: Field and academic visits will help students to develop observation skills, grasping ability, collect and interpret data and propose models that will help them to understand hypotheses and conclusions.
• PO 4 Analytical Reasoning: Through the interactions, students will develop skills of critical reading of texts, identifying gaps in knowledge, formulating scientific questions, and on will recognizing the synthesis of new ideas.
• PO 5 Scientific Reasoning: Skill oriented courses will provide details on principles, conduct of proper calibration and use of scientific instrumentation and appropriate use of scientific techniques in experimental design.
• PO 6 Self-directed Learning: Preparation of field reports helps them to present their results and discussion in a written format that is typically required for their future professions.
• PO 7 Reflective Thinking: All core courses with laboratory components will provide exposure to a wide range of research techniques, therein enhancing their understanding of the application of techniques in their domain.
• PO 8 Problem Solving: Students will develop the ability to reason, apply numerical concepts, and equations in their fields of study for interpreting scientific data and drawing relevant scientific conclusions.
• PO 9 Research-related Skills: Students undertaking a internship will have the opportunity to design, develop and execute their own research ideas in their experiments, thus expanding their knowledge of research methods and laboratory skills.
• PO 10 Lifelong Learning: Ability to understand the gaps in knowledge and skill, adapt to technological change, engage in self-directed learning.

Programme Educational Objectives (PEOs)

Within a few years of graduation, students of the programme will be able to:

• PEO1 – Professional Competence: Apply knowledge of Computer Science, Information Technology, Data Science, Artificial Intelligence and Machine Learning to develop effective solutions for real-world problems.
• PEO2 – Career and Higher Education: Pursue successful careers in IT industries, research organizations, government sectors and other technology-driven organizations, or pursue higher education and professional certifications.
• PEO3 – Innovation and Research: Demonstrate creativity, innovation, analytical thinking and research capabilities to address emerging challenges in computing and intelligent technologies.
• PEO4 – Professional Ethics: Practice professional ethics, social responsibility, teamwork and effective communication while working in multidisciplinary and multicultural environments.
• PEO5 – Lifelong Learning: Continuously update technical knowledge and skills in emerging areas such as Cloud Computing, Cybersecurity, Data Analytics, Artificial Intelligence, Machine Learning and Generative AI.

Programme Specific Outcomes (PSOs)

On successful completion of the programme, students will be able to:

• PSO1 – Computing and IT Skills: Apply programming, database, networking, software engineering, web technologies and information technology concepts to design and develop computing solutions.
• PSO2 – Data Science and Analytics: Collect, process, analyze and visualize data using statistical, computational and machine learning techniques to derive meaningful insights and support decision-making.
• PSO3 – Artificial Intelligence and Machine Learning: Design and implement AI and ML-based solutions using appropriate algorithms, tools and technologies for real-world applications.
• PSO4 – Emerging Technologies: Utilize emerging technologies such as cloud computing, big data, cybersecurity, Internet of Things, deep learning and generative AI to develop innovative applications.
• PSO5 – Research and Innovation: Identify technological challenges, conduct experiments, evaluate results and develop innovative solutions through project work, research and industry-oriented activities.