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JSS MAHAVIDYAPEETHA

    JSS Academy of Technical Education, Noida

Approved by All India Council for Technical Education (AICTE), New Delhi. UG programs are Accredited by National Board of Accreditation (NBA), New Delhi. Affiliated to Dr APJ Abdul Kalam Technical University, Uttar Pradesh, Lucknow
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B.Tech Computer Science (AI & ML)

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Academic Block 1

Introduction

The B.Tech program in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning (AI/ML) at JSS Academy of Technical Education, Noida is tailored to provide students with a deep understanding of AI and ML technologies. This program offers a comprehensive curriculum and state-of-the-art facilities to nurture the skills and knowledge required to excel in the world of AI and ML. The curriculum is regularly updated to reflect the latest industry trends, and students receive a solid foundation in computer science alongside specialized AI/ML courses. The department boasts an experienced faculty who are actively engaged in AI/ML research and bring industry insights to the classroom. Practical experience is emphasized through hands-on projects, lab sessions, and industry-relevant assignments, with students having access to advanced AI/ML tools and software. Opportunities for participation in ongoing research projects within the department are also available, contributing to the advancement of AI and ML technologies. Collaboration with industry partners provides students with exposure through internships, workshops, and guest lectures by industry experts. Graduates of this program are well-prepared for careers in data science, AI/ML engineering, research and development, and more, making them highly sought after in various industries. For admission criteria, program details, and application procedures, please refer to the official website of JSS Academy of Technical Education, Noida, or contact the department directly. This specialized B.Tech program equips students with the skills and knowledge required to excel in the dynamic field of AI and ML and positions them as valuable contributors to the technology industry.

# Program Outcomes :-The Graduates will be able to:
PO-1

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

PO-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.

PO-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.

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.

PO-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.

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.

As the name suggests, Artificial Intelligence (AI) is the intelligence used by a computer or a device. It is the ability of a machine to perform tasks that are usually performed by humans. For example, Chess-playing computers, self-driving cars, Alexa, Google Assistant, Siri, etc. All these are used in our day-to-day lives. They are all Artificial Intelligence (AI). On the other hand, Machine Learning is a sub-branch of AI. It is the application of AI in a way that a device learns from experience. Machine learning is done so that a device can improve itself on its own from the mistakes it makes. Both AI and Machine Learning is essential in today’s lives. We use AI in our daily routine.

B. Tech in Computer Science (Artificial Learning and 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 specialisation is designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning, analytics and visualisation technologies. The main goal of artificial intelligence (AI) and machine 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 behaviour (financial management), recognize faces or spoken speech, optimize robot behaviour 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.
Faculty Name
Qualification
(Specialization)
Desig.
Exp.
Yrs
DOJ
Nature of Association
Profile
Email-Id
1 Mr. Vimal Gupta B.Tech, M.Tech, (Ph.D.) Asst. Prof. & In-Charge HOD
20
01/04/2010
Regular
Click Here
vimalgupta
@jssaten.ac.in
2 Ms. Deepika Tyagi M.Tech
Assistant Professor
2.5
21/08/2023
Regular
Click Here
deepika.tyagi
@jssaten.ac.in
3 Mrs. Sakshi Aggarwal M.Tech
Assistant Professor
1
09/08/2023
Regular
Click Here
sakshi.aggarwal
@jssaten.ac.in
4 Ms. Megha Gupta M.Tech
Assistant Professor
4
15/09/2023
Regular
Click Here
megha.gupta
@jssaten.ac.in
5 Mr. Bijendra Tyagi M.Tech
Assistant Professor
9.5
01/01/2024
Regular
Click Here
Bijendra.tyagi
@jssaten.ac.in
6 Ms. Vishakha Chauhan M.Tech
Assistant Professor
9
14/03/2024
Regular
Click Here
vishakha.chauhan
@jssaten.ac.in

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