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About Department of Artificial Intelligence & Data Science

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About Artificial Intelligence And Data Science

Bachelor of Technology in Artificial Intelligence and Data Science is a 4-year undergraduate degree program, which is offered under the Engineering stream. Artificial Intelligence and Data Science programs, which are a vital component of a number of real-world applications, are prepared for the intelligent analysis of students.

In the graduate program in Artificial Intelligence, students are taught languages that are understood by computers or machines that enable people to engage with them to accomplish certain functionality. Some of the most prevalent machine languages taught to B. Tech students are the languages such as JAVA, Prolog, Lisp, R, and Python. With this course, students acquire disciplinary skills in areas such as stats, IT, machine learning and logic, data researchers, and employment chances in healthcare, commerce, e-commerce, social networking firms, climatology, biotechnology, genetics, and more.


VISION

To become Centre of Excellence in Artificial Intelligence & Data Science and to produce industry ready Machine Learning Engineers and Data Scientist to meet the challenges of IT industry.


MISSION
M1 To train the faculty in the area of Artificial Intelligence, Machine Learning, Deep Learning and Data Science and to make them expert in these areas.
M2 To educate students with the fundamental principles of Modern Computer Science.
M3 To train students with strong academic and technical skill sets in addressing the emerging challenges with a global perspective
M4 To provide innovation and research with the latest computer infrastructure

PROGRAM OUTCOMES
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.
PO4 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.
PO5 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.
PO6 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.
PO7 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.
PO8 Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9 Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO10 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.

PROGRAMMEE SPECFIC OUTCOMES
PSO-1 Understand, analyze and develop essential proficiency in the areas related to data science and artificial intelligence in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems
PSO-2 Ability to implement Artificial Intelligence and data science techniques such as search algorithms, neural networks, machine learning, and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship
PSO-3 Use modern tools and techniques in the area of Artificial Intelligence& Data Sciences.

PROGRAMMEE EDUCATION OBJECTIVES
PEO-1 To provide basic knowledge and skills in the field of Artificial Intelligence and Data Science.
PEO-2 Capable to quickly adapt to new technology in the field of Big Data, assimilate new information, and solve real world problems.
PEO-3 To pursue applied research in the advance field of Artificial Intelligence and Data Science and be committed to life-long learning activities.

Previous Question Papers

Facilities

Programming Language Lab

Programming refers to a technological process for telling a computer which tasks to perform in order to solve problems. You can think of programming as collaboration between humans and computers, in which humans create instructions for a computer to follow (code) in a language computers can understand.


Database Related Lab

Database Lab Platform is a unified solution that helps developers, DBAs, SREs, and QA engineers boost their work with PostgreSQL databases. They all can get their work done much faster thanks to the thin cloning of databases and the high level of automation of various tasks that the Platform offers.


Networks related lab

The laboratory networks were established to provide accurate and timely laboratory confirmation of infections, an essential component of disease surveillance systems. The laboratory networks provide high-quality surveillance data to help guide disease eradication, elimination and control programmers.


Algorithms related lab

This short course is designed for students who plan to learn about common data structures with efficient algorithms, solve LeetCode problems, and know state- of-the-art information techniques. The achievements of Algorithms Lab are listed below:


Faculty List

S.NO NAME OF THE FACULTY QUALIFICATION DISIGNATION
1 Dr.E V N Jyothi Ph.D ASSOCIATE PROFESSOR
2 Mr.K.Sai Susheel MTECH ASSISTANT PROFESSOR
3 Mrs.S.Sukanya MTECH ASSISTANT PROFESSOR
4 Mr.G.Subba Rao MTECH ASSISTANT PROFESSOR
5 Mr.K.Hari MTECH ASSISTANT PROFESSOR
6 Mr.CH.Suresh Babu MTECH ASSISTANT PROFESSOR
7 Mr.K.Chaithanya MTECH ASSISTANT PROFESSOR
8 Mr.S.Sundara Rajan MTECH ASSISTANT PROFESSOR
9 Mr.K.Mastan Rao MTECH ASSISTANT PROFESSOR

Syllabus

Toppers List

AIDS 2ND YEAR TOPPERS LIST
ROLL NUM NAME CGPA
21KQ1A5491 R KALYANI 9
21KQ1A5495 T BHARGAVI 8.8
21KQ1A5471 B AMULYA 8.9
21KQ1A5447 K SAI 9
21KQ1A5422 SK KOUSER 9

AIDS -3RD YEAR TOPPERS LIST
ROLL NUM NAME CGPA
20KQ1A5416 K.Madhavi 9.3
20KQ1A5430 S.Sai Javali 9.2
20KQ1A5428 SHAIK. SEEMA 9.2
20KQ1A5404 A.Dedeepya 9.1
20KQ1A5424 P.Kousar 9
20KQ1A5433 T.Saathwika 9
20KQ1A5463 V.Vijay prakash 9
20KQ1A5435 V.Venkata Jahnavi 8.9

STUDENT ACHIEVEMENTS

Faculty ACHIEVEMENTS

RESEARCH GROUPS

Innovations