An Autonomous Institute-UGC | B.TECH, M.TECH, MBA, Polytechnic

Admissions for all UG courses (2023-24)
CSE ( AI & ML)> Admissions for all UG courses (2023-24) is now open under Management. > Application process: Interested candidates can apply for UG courses under Management quota by visiting the official website of the college or university or by obtaining the application form Filled the college campus. The application form must be filled with all the necessary details and submitted along with the required documents and the application

ABOUT THE DEPARTMENT

Computer Science and Engineering (Artificial Intelligence and Machine Learning)

The Department of CSE-Artificial Intelligence and Machine Learning at Ellenki College of Engineering and Technology was established in 2020, with an intake of 90 students. Our CSE(AI-ML) program offers advanced learning solutions that impart knowledge of cutting-edge innovations such as machine learning, deep learning, artificial intelligence, and more. This specialization is designed to enable our students to build intelligent systems, software, or applications with a combination of artificial intelligence, machine learning, analytics, and visualization technologies.

The main goal of artificial intelligence (AI) and machine learning (ML) is to provide intelligence through complex programming to solve a given problem. In the real world, many successful applications are based on machine learning, including systems that analyze past sales data to predict customer behavior, financial management, face recognition, speech recognition, image processing, optimize robot behavior, recommender systems in e-commerce, and more, so that tasks can be completed using minimum resources.

Ample career opportunities exist in both the public and private sectors, including the healthcare industry, manufacturing, e-commerce, social networks, and more. The jobs in AI include software analysts and developers, computer scientists and computer engineers, AI algorithm specialists, research scientists, AI and ML engineers, machine learning and artificial intelligence scientists, AI software engineers, and more.

Graduate Courses (B.Tech)

Academic intake details 

S.No

BRANCH

COURSE TYPE

DURATION

INTAKE

1

CSE-Artificial Intelligence and Machine Learning

Full Time

4 Years

90

Information

Vision

To accomplish an admirable standard of quality education by utilizing the latest technologies, innovations to be applicable for academia and industry which helps society in large.

Mission
  • To evolve professional who is proficient in the area of AI-ML
  • To impart principle-based education and contribute to the innovation of computing and learning-based systems.
  • Our Endeavour is to try new advancements in high-end computing hardware and software for society.
PEOs

PROGRAM EDUCATIONAL OBJECTIVES (PEOS)

PEO-1: Pursue a thriving professional career in IT-enabled industries.

PEO 2: Pursue enduring learning in generating inventive engineering solutions using research and composite problem-solving abilities.

PEO 3: Demonstrate professionalism, principles, inter-personal skills and incessant learning to develop management qualities.

POs

PROGRAM OUTCOMES (POS)

Engineering Graduates will be able to satisfy these NBA graduate attributes:

  1. Engineering knowledge:Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. Problem analysis:Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. Environment and sustainability:Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  8. Ethics:Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  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.
  11. 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.
  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.
PSOs

PROGRAM SPECIFIC OUTCOMES(PSO’S)

    1. Professional Skills and Foundations of Software development:Ability to analyze, design and develop applications by adopting the dynamic nature of Software developments
    2. Applications of in the fields of Artificial Intelligence and Machine learning: Ability to use knowledge in artificial intelligence and machine learning to solve real world problems and identify the research gaps and render solutions with innovative ideas.

    solutions with innovative ideas

ADMISSIONS FORM 2023

Department Overview

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