About the Department

The Department of Artificial Intelligence and Data Science (AI&DS) offers a B.Tech. Program in Artificial Intelligence and Data Science, launching a new intake of 90 students starting from the academic year 2022-2023 with the vision of producing graduates with advanced global competencies in AI and Data Science, fostering successful careers, lifelong learning, and dedication to driving ethical social development initiatives. The curriculum is designed as an Outcome-Based Education model and includes industrial internships to align students with current industry trends. The department is developing state-of-the-art infrastructure and aims to foster both technical skills and a robust research culture, featuring a Centre of Excellence in AI. AI&DS department collaborates with four IT companies, In association with ICT ACADEMY we have the center of excellence in Oracle, It also hosts a chapter of the Computer Society of India (CSI), enhancing its professional networking and promoting collaboration in computer science and technology and it has established a campus agreement with Microsoft. Career opportunities include Big Data Engineer, Data Scientist, AI Engineer, Full Stack Developer, Software Architect, Robotics Engineer, etc.,

Vision

To produce graduates with global competency, career success, and lifelong learning who are passionate about social development and ethical values.

Mission

To provide high-quality experimental learning to get expertise in modern Artificial Intelligence tools and to meet the current needs of the industry.
To create a learning atmosphere that fosters inventiveness, problem-solving abilities, and a sense of ethical and social Obligations.

Program Outcomes (POs):

  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. Development of solutions:Design/ 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 modeling 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.

Our Faculty

Our Artificial Intelligence (AI) and Data Science (DS) faculty members are dedicated to providing students with a comprehensive and current education in these rapidly evolving fields. They bring a wealth of knowledge and experience, covering a wide range of specialized domains such as machine learning, deep learning, natural language processing, big data analytics, data mining, and data visualization.

Dr. B. Baron Sam,
HOD & Associate Professor
baronsam@dmiengg.edu.in
Mrs. G. Lingeshwari M.E.,
Assistant Professor
lingeshwari@dmiengg.edu.in
Ms. S. Reny M.E.,
Assistant Professor
reny@dmiengg.edu.in
Mrs.Sahaya Reema F,
Assistant Professor
sahayareema@dmiengg.edu.in
Mrs. S. Aloysius Jelcy M.E.,
Assistant Professor
aloysiusjelcy@dmiengg.edu.in
Mrs. Ajila Jaya Reeta C M.Tech.,
Assistant Professor
ajila@dmiengg.edu.in
Mrs. Jeba Christy M.Tech.,
Assistant Professor
christy@dmiengg.edu.in

Lab Facilities

Our Artificial Intelligence (AI) and Data Science (DS) Lab is equipped with cutting-edge technology and resources to provide students with a comprehensive learning experience. The lab is designed to support a wide range of activities, from theoretical studies to practical applications, ensuring that students are well-prepared for careers in AI and data science.

Our Lab Features
  • Advanced Computing Resources: Our lab boasts high-performance computing systems that are essential for running complex AI algorithms and data processing tasks. With powerful CPUs, GPUs, and ample storage, students can handle large datasets and perform intensive computations without any hindrance.
  • Research and Development Support: We are committed to supporting innovative research and development in AI and data science. The lab provides access to extensive datasets, academic journals, and research papers, along with guidance from experienced faculty members. This environment encourages students to engage in cutting-edge research and contribute to advancements in the field.
  • Specialized Equipment: The lab is furnished with specialized equipment to support AI and DS projects. This includes robotics kits for AI-powered automation projects, IoT devices for data collection and real-time analytics, and advanced sensors for various research applications. These resources enable students to work on a diverse range of projects, from natural language processing to computer vision and beyond.

AI & DS Lab


The lab has access to the latest software tools and platforms commonly used in the industry. This includes popular programming languages like Python and R, machine learning libraries such as TensorFlow and PyTorch, and data analysis tools like Apache Spark and Hadoop. Students can also work with cloud computing services like AWS and Google Cloud Platform for scalable computing solutions.