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.
Programmes offered
Under Graduate
Intake
B.Tech. (Artificial Intelligence and Machine Learning)
180
Teaching Staff Details
S.No
NAME OF THE STAFF
DESIGNATION
QUALIFICATION
PHOTO
PROFILE LINK
1
Dr. Maganti Venkatesh
Associate Professor & HOD
Ph.D
2
Mr. N S L Kumar Kurumeti
Associate Professor
M.Tech., (Ph.D)
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3
Dr.Suneetha Racharla
Associate Professor
Ph.D
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4
Mr.Vengalapudi Appalakonda
Assistant Professor
M.Tech
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5
Mr. Grandhi Siva Shankar
Associate Professor
B.Tech., M.Tech., (Ph.D.)
6
Mr. P V V S D Nagendrudu
Assistant Professor
M.Tech
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7
KOLLI SRINU
Assistant Professor
M.Tech
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8
Mr. ALISHA MD
Sr.Assistant Professor
M.Tech
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9
Mrs. K. Kavya Ramya Sree
Assistant Professor
B. Tech., M.Tech., (Ph.D)
10
KOTTAPALLI SIVA PAVANI
Assistant Professor
M.Tech
Other Supporting Staff
S.No
NAME OF THE STAFF
QUALIFICATION
DESIGNATION
EXPERIENCE
1
Mrs. Kondrapu Dharani
B.Sc. Computers
Programmer
2 Months
2
Miss. K. Durga Bhavani
B.Sc. Computers
Programmer
1 Year 5 Months
3
Miss. Maddala Divya
Diploma
Junior Assistant
10 Months
Our Vision
To become a recognized centre of excellence in the field of AIML that fulfil the needs of industry and society.
Our Mission
M1:
Impart the knowledge through states-of-the-art concepts, tools and techniques in Artificial Intelligence.
M2:
Promote technical competence by collaborating with Industries to provide solutions for future challenges.
M3:
Inculcate ethics, environmental and societal consciousness for social responsibility.
M4:
Build leadership and life-long learning skills to ensure the holistic development of stakeholder.
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Program educational objectives
PEO 1:
Apply core concepts in mathematics and computer science with Machine Intelligence 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 Machine Intelligence.
PEO 3:
Work in a collaborative environment and also lead the team by understanding the ethical, societal and financial impact of their work.
Program specific outcomes
PSO 1:
Apply the core concepts of computational, Machine Intelligence, Data Science and optimized algorithms to produce efficient solutions.
PSO 2:
Apply technical and research skills in AIML to become a successful Graduate/Entrepreneur/Machine Intelligence Expert through innovative tools and techniques by providing solutions in the areas of engineering, industry and society.
Program outcomes
PO 1:
Engineering Knowledge: Apply knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution of complex engineering problems.
PO 2:
Problem Analysis: 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/ Development of Solutions: Design solutions for complex engineering problems and design system 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:
Modern Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering and IT tools including prediction and modelling to complex engineering activities with an under- standing of the limitations.
PO 6:
The Engineer and Society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice.
PO 7:
Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate knowledge of and need for sustainable development.
PO 8:
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
PO 9:
Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams and in multidisciplinary settings.
PO 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.
PO 11:
Project Management and Finance: Demonstrate knowledge and understanding of 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.
PO 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.
Co-Curricular Activities
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2023-24
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2022-23
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2021-22
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2020-21
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2019-20
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Special Programmes for Advanced learners and Slow learners