With the new technologies coming into the global world, our Aditya Engineering College has taken a step forward to introduce a new course which offers 4 year B.Tech course in Artificial Intelligence and Machine Learning. This course has been introduced in the curriculum in the academic year 2021 with the intake of 60 students. It is extended with the intake of 180 students from academic year 2022. This course provides a cutting-edge exploration of programming, mathematics, and analytics to create out-of-the-box designs with digital technologies necessary to drive innovation across borders and sectors.

Artificial Intelligence and Machine Learning is a branch of study that includes theories, standards, methods and innovations of various different domains like mathematics, cognitive science, electronics and embedded systems to make intelligent systems that mimic human behaviour.

Artificial Intelligence and Machine Learning focus on collecting, categorizing, analyzing and interpreting data.

It is a specialised branch that deals with the development of embedded systems like robotics and IoT based applications.

It also incorporates the concepts of machine learning and deep learning model building for solving various computational and real-world business problems.

Artificial Intelligence and Machine Learning is an appropriate course for those who like to develop various innovative and intelligence solutions to solve complex industrial and business problems. This can contribute in industrial automation, information technology and other sectors like healthcare, agriculture, wearable, space, and meteorology through analysis of raw data, extract knowledge or intelligence from that and design, develop, support and test AI and ML based systems and embedded applications.

AI and ML graduates can also showcase their expertise in knowledge management, mobile and distributed application development, intelligence web/e-commerce development, database administration, computer hardware, networking, education and training and decision support systems using machine learning concepts with the help of the latest tools and technologies.

We are very happy to say that we have signed MOUs with various standard assessment organizations like Co Cubes, AMCAT, Elitmus etc.

M1:

Impact the knowledge through states-of-the-art concepts, tools and techniques in Artificial Intelligence and Machine Learning

M2:

To promote technical competence in AIML graduates that satisfies the needs of the Industry and societal challenges.

M3:

Inculcate ethical and environmental consciousness, leadership qualities and life-long learning that ensures the holistic development of students.

M3:

Establish centers of excellence in leading areas of computing with Artificial Intelligence and Machine Learning

To achieve excellence in the field of AIML and nurture the professionals, to build sustainable and intellectual solutions with natural intelligence that meets the beneficiary of industry and society

PEO 1:

Apply core concepts, software engineering and AIML principles to solve complex computing problems and produce optimized solutions.

PEO 2:

Pursue higher education and research activities through innovative ideas and latest technology-driven projects in the domain of AIML.

PEO 3:

Work in a collaborative environment and also lead the team by understanding the ethical, societal and financial impact of their work.

PO 1:

Apply knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution of complex engineering problems.

PO 2:

Identify, formulate, research literature and analyze complex engineering problems, reaching substantiated conclusions using first principles of mathematics, natural sciences and engineering sciences.

PO 3:

Design solutions for complex engineering problems and design systems, components or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations

PO 4:

Conduct investigations of complex problems using research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions.

PO 5:

Create, select and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering activities, with an understanding of the limitations.

PO 6:

Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineeringpractice.

PO 7:

Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate knowledge of, and need for sustainable development.

PO 8:

Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.

PO 9:

Function effectively as an individual, and as a member or leader in diverse teams and in multidisciplinary settings.

PO 10:

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

PO 11:

Demonstrate knowledge and understanding of engineering management principles and apply these to one’s own work, as a member and leader in a team and to manage projects in multidisciplinary environments

PO 12:

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.

PSO 1:

Apply the core concepts of computational and optimized algorithms to produce efficient and effective solutions

PSO 2:

Apply the technical and research capability skills in AIML using innovative tools and techniques to provide solutions in the areas of engineering, industry and society to become successful graduate/entrepreneur.

Co-Curricular Activities