CSE (Artificial Intelligence and Machine Learning)
The Department of CSE (AI-ML) was started in the year 2023 with an intake of 60, as an Emerging Branch in the area of Computer Science and Engineering. Later, the intake is increased to 120 in the 2024-25 academic year.
A relatively new program in computer science, artificial intelligence (AI) is quickly gaining ground in a wide range of industries, including healthcare, security, entertainment, education, autonomous vehicles, intelligent robots, space exploration, speech recognition, stock trading, and many more. Our lives have changed significantly as a result of AI and its uses. By imitating human intelligence, artificial intelligence (AI) seeks to instill intelligence in robots. An application of artificial intelligence (AI) called machine learning (ML) aims to give machines the capacity for self-learning. The digital revolution is greatly aided by AI and ML, which have also produced a large number of job prospects. Professional engineers with training in these technologies are in high demand. This program offers essential degrees that elevate the status of the student industry.
To emerge as a center of excellence in Artificial Intelligence and Machine Learning, empowering students to become innovative professionals and ethical leaders who contribute to societal advancement through intelligent technologies.
MISSION
To impart quality education in computer science with a strong foundation in AI and ML technologies.
To promote research, innovation, and practical problem-solving through real-world projects and collaborations.
To foster industry-academia interaction for internships, certifications, and placements.
To inculcate professional ethics, social responsibility, and leadership qualities in students.
To support continuous learning and adaptation to technological advancements.
Program Objectives (POs)
PO1: Engineering Knowledge: Apply knowledge of mathematics, science, and engineering fundamentals.
PO2: Problem Analysis: Identify and analyze complex problems using principles of computing and AI/ML.
PO3: Design/Development of Solutions: Design software or systems that meet desired needs.
PO4: Conduct Investigations: Use research-based knowledge to conduct experiments and analyze data.
PO5: Modern Tool Usage: Create, select, and apply modern tools and techniques in AI/ML.
PO6: Engineer and Society: Assess societal, legal, and cultural issues relevant to AI solutions.
PO7: Environment and Sustainability: Understand the impact of AI/ML in societal and environmental contexts.
PO8: Ethics: Commit to professional ethics and responsibilities.
PO9: Individual and Team Work: Function effectively as an individual and in diverse teams.
PO10: Communication: Communicate effectively in both technical and non-technical contexts.
Program Educational Objectives (PEOs)
PEO1: Apply core knowledge of computer science and AI/ML techniques to solve real-world problems effectively.
PEO2: Pursue higher education, research, or successful careers in leading industries and organizations.
PEO3: Demonstrate professional ethics, teamwork, communication, and leadership skills in multidisciplinary environments.
PEO4: Continuously upgrade their knowledge and skills in emerging areas through lifelong learning.
Program Specific Outcomes (PSOs)
PSO1: Apply AI and ML concepts to build intelligent systems and data-driven solutions.
PSO2: Develop and deploy scalable software using modern tools and platforms in AI/ML domains.
PSO3: Take part in research or develop new ideas in AI & ML, and get ready for higher studies or projects.
Clarity – developing the Vision
Having clarity of purpose and a clear picture of what you desire, is probably the single most important factor in achievement. Why is Clarity so important?
Without clarity, you send a very garbled message out to the Universe. We know that the Law of Attraction says that we will attract what we focus on, so if we don’t have clarity, we will attract confusion.
The laboratories are the backbone of engineering course of study, the Laboratory instruction develops students' experimental skills, ability to work in teams and communicate effectively, learn from failure, and be responsible for their own results. We have the following laboratories with full-fledged faculties.
AIML Lab
The AIML Lab is dedicated to fostering advanced research and practical learning in the domains of Artificial Intelligence and Machine Learning. The lab is equipped with high-performance computing resources, AI development frameworks, and datasets to support projects in deep learning, natural language processing, computer vision, and data analytics. Students engage in hands-on implementation of algorithms, model training, and participate in interdisciplinary AI-driven projects.