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About the Department of Artificial Intelligence and Machine Learning


Artificial Intelligence (AI) is all about simulating human intelligence processes by machines, especially computer systems. The field involves developing algorithms for a dynamically changing environment. In 1763, Prof. Thomas Bayes developed a framework for reasoning the probability of occurrence of a future event based on the probabilities of prior events; to Prof. John McCarthy, who introduced Artificial intelligence to the world in 1956, AI has seen many implementations and research challenges. The field is in continuous transition to achieve maturity to handle the 21st-century requirements of industries and society.

According to a Mckinsey report, telecommunication, automotive, and financial services are high-end adopters of AI. Retail industries, Media/entertainment, and CPG, are the middle-level adopters, whereas education, health care, and travel/tourism industries are low-end adopters, as the industries achieve digital maturity, the levels of these adoptions also vary.

AI & ML empower enterprise-level problem solving with the application of cutting-edge technologies with a true sense of digital transformation, reducing the production/service costs, an increased degree of customer satisfaction with quality outcomes. With an increased budgetary provision for AI & ML technologies R&D, developed and developing countries have targeted achieving AI supremacy in the coming decade. The Govt. of India, in its Budget 2020, has created provisions for Rs. 3000 crores for AI skills development, digitalization of 100,000 Gram Panchayat through the Bharatnet initiative, setting up data center parks across the country and so on.

AI & ML impact us and our society in many ways, including social, economic, legal, political, and regulatory impacts. AI-integrated solutions have occupied many daily activities, and AI push is already seen in industrial growth rates. Many countries have started publicizing their National-level AI strategies, including the Indian AI stack by NITI Aayog. Indian AI stack has proposed to adopt a three-pronged approach, which includes creating proof-of-concept of AI projects in various areas, building an AI-based start-up ecosystem in India, and Collaborating with experts and stakeholders.

The first batch of Batchelor of Engineering in Artificial Intelligence(AI) and Machine learning(ML) at RV College of Engineering started in 2021 with an intake of 60,Intake has been raised to 120 from the year 2023. The curriculum of the AI&ML program is designed to provide necessary basics in Computer science engineering with specialized knowledge and skills in Artificial Intelligence, Machine Learning, Deep Learning, Reinforcement learning, NLP, HCI, Data Science, Meta Heuristics, Computer Vision, Business Intelligence, and other interdisciplinary areas.

Department comprised of faculty members with long academic experience in the domain and pursuing research activities in all related disciplines of Artificial Intelligence and Machine learning.


  • To develop sustainable solutions for the greater good of society, through quality engineering education in Artificial Intelligence and Machine Learning, with innovation, research, and consultancy activities.


  • To impart cutting-edge knowledge and skills in Artificial Intelligence and Machine Learning with a foundation in Computer Science and Engineering.
  • To promote innovative research and development in Artificial Intelligence and Machine Learning and its allied fields in collaboration with industries.
  • To prepare the students for solving real-world problems by imparting engineering skills through experiential learning mode.

  • To provide a pleasant environment in pursuit of excellence by keeping high personal and professional values and ethics.

Program Educational Objectives(PEOs)

PEO1:Develop graduates capable of applying the principles of Mathematics, Science, core Computer Science Engineering with Artificial Intelligence, and Machine learning knowledge to solve real-world interdisciplinary problems.

PEO2:To develop the ability among graduates to analyze and understand the state of the art technologies and industrial practices in the Artificial Intelligence and Machine-learning domain through experiential learning.

PEO3:Develop graduates who will exhibit cultural awareness, teamwork with professional ethics, and practical communication skills with an inspiration to understand the social and economic impact of Artificial Intelligence and Machine learning in the foreseeable future.

PEO4:Prepare employable graduates for the right roles in industries / to become entrepreneurs to achieve higher career goals or take up higher education to pursue lifelong learning.

Program Specific Objectives(PSOs)

PSO1: Problem Solving and Analysis

The student will be able to:

1. Appreciate the importance of Mathematics, Electronics and Sensors, Data organization and Algorithms, Design thinking, and Software Engineering principles in building Intelligent Computational Systems.

2. Learn the applicability of Artificial Intelligence and Machine learning algorithms to solve real-world problems.

3. Identify the need for Deep learning, Computer vision, and Natural language processing to develop intelligent software products focusing on application performance.

4. Display team participation, good communication, project management, and documentation skills.

PSO2: Experiential Learning

The student will be able to:

1. Demonstrate the application of knowledge to develop intelligent software programs for various use case scenarios in industrial sectors like healthcare, agriculture, education and skilling, governance, energy, automotive, infrastructure, banking and finance, and manufacturing.

2. Participate in planning and developing enterprise-level solutions with cutting-edge technologies, displaying group dynamics and professional ethics.

3. Employ experiential learning throughout the program to enrich the practical aspects to reach state of the art in the domain.

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