Regular curriculum review processes and collaboration with industry experts are essential, says Dr Soman K.P., an expert on research and teaching in Artificial Intelligence and Data Science.
Dr Soman K.P. currently serves as the Dean of the School of Artificial Intelligence (AI), Head and Professor at Amrita Center for Computational Engineering and Networking (CEN), Coimbatore Campus. He has more than 27 years of research and teaching experience in Artificial Intelligence (AI) and Data Science-related subjects at Amrita Vishwa Vidyapeetham, Coimbatore. He has authored over 500 publications in reputed journals and currently, he is working on AI applied to DNA sequence analysis, Reinforcement learning for Robotics Control, Computer Vision, and Cyber-Physical Systems. Excerpts from an interaction with Dr Soman K.P.:
Q: What are the prerequisites for pursuing a B. Tech in AI & Data Science?
A: The prerequisites for pursuing a B. Tech in Artificial Intelligence & Data Science at Amrita Vishwa Vidyapeetham Coimbatore Campus may include the following: Educational Qualifications: You should have completed high school or an equivalent qualification recognized by the university. Typically, this includes passing the qualifying examination, such as 10+2 or its equivalent, with a minimum percentage requirement as specified by the institution; Subject Requirements: You should have studied specific subjects in your high school curriculum, which include Mathematics and Physics. The specific subject requirements may be outlined by the university or college offering the program; Entrance Examination: Amrita Vishwa Vidyapeetham conduct an entrance examination for admission to their B. Tech programs. You may need to qualify in this examination to be eligible for admission; Mathematics Background: A strong foundation in mathematics is essential for studying AI. You should have a good understanding of topics such as algebra, calculus, probability, and statistics. Knowledge of linear algebra and discrete mathematics can also be beneficial; Programming Skills: Proficiency in programming is crucial for AI studies. Familiarity with programming languages like Matlab, Python, Java, or C++ is essential. At the entry point, Programming knowledge is not mandatory but a desire and attitude for learning and practicing it on daily basis is essential for successful completion of the course; Strong Analytical and Problem-Solving Skills: AI involves solving complex problems and requires analytical thinking. Developing strong problem-solving skills is important for successfully studying AI.
Q: What are the core subjects and topics covered in the B. Tech AI & DS curriculum?
A: The core subjects and topics covered in the B. Tech AI and DS curriculum are: Mathematics for Intelligent systems (Linear Algebra, Calculus, Optimization theory, Probability and Statistics); Artificial Intelligence Fundamentals; Programming and Software Development; Data Science and Analytics; Computer Vision and Image Processing; Natural Language Processing (NLP); Robotics and Automation and Project Work
Q: How is the B. Tech AI program structured? Is it theory-heavy or practical-oriented?
A: The B.Tech AI and Data Science program at Amrita Vishwa Vidyapeetham is designed to provide students with a balanced mix of theoretical knowledge and practical skills. The program aims to equip students with a strong foundation in AI and data science principles along with hands-on experience in applying these concepts to real-world problems. The program is structured to include Core Courses, Practical Labs, Elective Courses, Industry Collaboration and Project Work.
Q: What are the faculty credentials and expertise in the AI department?
A: School of AI recruited faculty and researchers from various domains (Computing Science, Computer Science, Electrical and Electronic Engineering, Mechanical Engineering, Biology and Bioinformatics, Material Science Mathematics etc ) and put under one umbrella to provide truly integrated interdisciplinary ambience in the teaching , research and learning process.
It is utilizing 25 years of research and development experience of the Centre for Excellence in Computational Engineering and Networking of Amrita University which was spearheading research in the university in the areas of Natural Language Processing of Indic Languages, Signal and Image Processing, Computer Vision, Data Analytics, IoT and Cyber Security. Most faculty have M.Tech/PhD from Premier Institutions. Some have postdoctoral experience from Industry and foreign universities. The Centre has produced several Computational linguistics and Cyber Security experts for the country.
Q: Are there any research opportunities or industry collaborations available?
A: School of AI in addition to existing facility is establishing new research labs for doing research in Large Language models, Robotics and Automation, Materials Science and discovery Bioinformatics and Drug Discovery, and Cyber Security. We have plans to introduce industry projects right from the second semester.
Q: Are there any internship or industry programs to gain practical experience?
A: The entire course is practice oriented. Top 20% students will be interfaced to industry right from second semester, all others in subsequent semesters depending on the maturity. By third year end, all will be given chance to do industry projects.
Q: Why do we need AI and Data Science and can you connect it with some real-time applications?
A: AI (Artificial Intelligence) and Data Science have become essential in today’s world due to their numerous applications and the potential they hold for solving complex problems. Ssome real-time applications that demonstrate the significance of AI and Data Science are in areas of Healthcare, Finance and Banking, Transportation and Logistics, E-commerce and Recommendation Systems, Manufacturing and Supply Chain, Natural Language Processing and Virtual Assistants, Image and Speech Recognition, and Social Media and Sentiment Analysis.
Q: What are the latest trends and advancements in AI, and how is the curriculum updated to reflect these changes?
A: AI is a rapidly evolving field, and staying updated with the latest trends and advancements is crucial for an AI curriculum. Some of the latest trends and advancements in AI include Deep Learning, Reinforcement Learning, Explainable AI, Generative AI, AI Ethics and Responsible AI and Edge Computing and IoT. To reflect these changes, universities and institutions typically update their AI curricula by introducing new courses, revising existing courses, and incorporating the latest advancements and research findings.
Faculty members, who stay active in research and industry collaborations, play a vital role in updating the curriculum based on emerging trends. Guest lectures, workshops, and industry partnerships may also provide avenues for students to learn about the latest advancements in AI. It’s worth noting that AI is a fast-evolving field, and the curriculum must be flexible and adaptable to keep pace with new developments. Regular curriculum review processes, collaboration with industry experts, and monitoring the evolving needs of the field help ensure that AI curricula stay current and relevant.