B. Tech in Artificial intelligence & Machine Learning is an undergraduate programme with advanced learning solutions imparting knowledge of advanced innovations like machine learning, often called deep learning and artificial intelligence.
This specialization is designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning, analytics and visualization technologies. The main goal of artificial intelligence (AI) learning is to program computers to use example data or experience to solve a given problem. Many successful applications based on machine learning exist already, including systems that analyze past sales data to predict customer behavior (financial management), recognize faces or spoken speech, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data.
This programme discusses AI methods based in different fields, including neural networks, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions.
|S.No||Year of ESTD||Name of the Course||Intake|
|1||2020||B.Tech – Artificial Engineering||60|
- To provide high quality technical education to students that will enable life-long learning and build expertise in advanced technologies in Computer Science and Engineering.
- To promote research and development by providing opportunities to solve complex engineering problems in collaboration with industry and government agencies.
- To encourage professional development of students that will inculcate ethical values and leadership skills while working with the community to address societal issues.
- Engineering knowledge:Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution of complex engineering problems.
- Problem analysis:Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural science and engineering sciences.
- Design/development of solutions:Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal and environmental considerations.
- Conduct investigations of complex problems:Use research based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
- Modern tool usage:Create, select and apply appropriate techniques, resources and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
- The engineer and society:Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
- Environment sustainability:Understand the impact of the professional engineering solutions in the societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
- Ethics:Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
- Individual and team work:Function effectively as an individual and as a member or leader in diverse teams, and in multidisciplinary settings.
- 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.
- Project management and finance:Demonstrate knowledge and understanding of the 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.
- Lifelong learning:Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broader context of technological change.
Program Educational Objectives
- PEO 1:
Graduates will provide solutions to difficult and challenging issues in their profession by applying computer science and engineering theory and principles.
- PEO 2:
Graduates have successful careers in computer science and engineering fields or will be able to successfully pursue advanced degrees.
- PEO 3:
Graduates will communicate effectively, work collaboratively and exhibit high levels of professionalism, moral and ethical responsibility.
- PEO 4:
Graduates will develop the ability to understand and analyze engineering issues in a broader perspective with ethical responsibility towards sustainable development.
Program Specific Outcomes
- PSO 1: Problem Solving Skills – Graduate will be able to apply computational techniques and software principles to solve complex engineering problems pertaining to software engineering.
- PSO 2: Professional Skills – Graduate will be able to think critically, communicate effectively, and collaborate in teams through participation in co and extra-curricular activities.
- PSO 3: Successful Career – Graduates will possess a solid foundation in computer science and engineering that will enable them to grow in their profession and pursue lifelong learning through post graduation and professional development.
Head of the Department
1. He has been selected as a “Most Promising Educators in Higher Education Across India 2019 “by uLeKtz wall of Fame.
2.He has been selected for “Maximum Patents filed in the Year 2019 “ in Indian Book of Records 2021 Edition .
Dr.Siva Shankar S – B.Tech M.Tech,Ph.D, MISTE.,MIAENG.,MCSTA
Associate Professor & Head(AI)
Mobile : +91 9566577774
E Mail : email@example.com
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. It refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
The Department has well equipped lab facilities and enough systems to train students to provide Hands on Experience.
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