B.Tech Artificial Intelligence and Machine Learning

About the Department

Vision and Mission

Prog. Edu Objectives & Outcomes

About the Department

The department of Artificial Intelligence and Machine Learning has been established in the year 2022, recognized by AICTE. Artificial Intelligence specialization will create engineers, who can build solutions, with intelligence as humans.

The Department conducts co-curricular activities such as Guest Lectures, Seminars, Training programs, Workshops, etc. The Department also organizes industrial visits to help students to update their knowledge.
An exclusive Training and Placement cell is functioning for providing continuous training and placement assistance to the students during their course of study. The students are trained by internal trainers and industry experts with various training partners to improve their employability skills like soft skills, technical, analytical and logical skills. Apart from training, to enhance the innovative thinking and managerial skills of young minds, they are encouraged to organize and participate in various events like paper presentations, technical symposia and project presentations.
Currently, the world is being driven digitally with technology and data being present everywhere. It is because many leading companies in the world today, such as Face book, Google and Uber, make machine learning as a central part of their operations. The machine learning market size has been steadily growing. It is a type of data mining that allows computers to learn on their own experience.
Nowadays, it's not an exaggeration to say that each of us encounters machine learning multiple times daily. Until the 1960s AI and ML were more or less synonymous, but thereafter they diverged and now they are rampant in the tech industry, mass media and academia.
Data scientists and machine-learning engineers are two of the top-ranked jobs globally. Professionals with critical expertise in the domain of data science and machine learning are highly sought after by tech and finance organizations.
This course dives deep into the foundational as well as advanced concepts of data science and machine learning to enable students to devise practical solutions in real context.
The department provides state-of-the-art computing facilities to the students enabling them to stay a step ahead. They are exposed to various opportunities such as in plant training, internships, and workshops during their course of study.

Vision and Mission

VISION

To be a center of excellence in the field of Artificial Intelligence and Machine Learning applications through appropriate use and diffusion of emerging techniques.

MISSION

To develop students with strong capabilities in Artificial Intelligence by continuously enhancing teaching and learning with state-of-the-art technologies.
To provide high-quality, value-based education to gain competence in Artificial Intelligence and Machine learning in terms of research and innovation activities.
To implement engineering solutions for the benefit of society by the use of AI and ML.

Programme Educational Objectives(PEOs)

PEO 1: To perform well in their professional career by acquiring enough knowledge in the domain of Artificial Intelligence and Machine Learning.
PEO 2: To enable graduates to research, design and implement AI/ML products and services with effective Communication and Entrepreneurial Skills.
PEO 3: To modernize the students with evolving technology and use it for career advancement.

Programme Outcomes (POs)

PO1: Engineering knowledge:
Apply the knowledge of Mathematics, Science, Engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO2: 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.
PO3: 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.
PO 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.
PO 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.
PO 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.
PO 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.
PO 8: Ethics:
Apply ethical principles and commit to professional ethics and responsibilities and norms of the 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.
PO11: 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.
PO12: 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.

Programme Specific Outcomes (PSOs)

PSO1: Develop models in Data Science, Machine learning, Deep learning and Big data technologies, using AI and modern tools.
PSO2: Create solutions for interdisciplinary AI problems through acquired programming knowledge in the respective domains fulfilling with real-time constraints.

Department of Artificial Intelligence and Machine Learning

About the Department

Vision and Mission

VISION

MISSION

Programme Educational Objectives(PEOs)

Programme Outcomes (POs)

Programme Specific Outcomes (PSOs)

Admissions

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