Artificial Intelligence & Data Science

OVERVIEW

Artificial Intelligence and Data Science, as branches of engineering, blend methodologies from statistics, cognitive science, computing, and information science to extract insights from data. This knowledge drives intelligent business decisions by collecting, categorizing, strategizing, analyzing, and interpreting data. These fields specialize in developing data-driven solutions, data visualization tools, and techniques for handling big data, incorporating machine learning and deep learning to solve computational problems.

Suitable for those interested in creating intelligent business solutions, AI and Data Science offer lucrative career opportunities. Graduates can design and implement AI and DS-based software solutions, utilizing the latest tools and technologies to solve real-world problems. They acquire skills in data handling, knowledge extraction, and various application developments, contributing significantly to industries like manufacturing, e-commerce, finance, and healthcare.

Vision and Mission

To be a vibrant nodal center for Artificial Intelligence and Data Science Education, Research that make the students to contribute to technologies for IT, IT-Enabled Services; to involve in innovative research on thrust areas of data science industry and academia; to establish start-ups supporting major players in the industry.
  • DM1: Emphasize project based learning by employing the state-of art technologies, algorithms in software development for the problems in Data science using AI.
  • DM2: Involve stakeholders to make the students industry ready with training in skill-oriented computer application software.
  • DM3: Facilitate to learn the theoretical nuances of AI techniques, Computer Engineering courses and motivate to carry out research in both core and applied areas of AI.

PEO's and PSO's

  1. PEO 1: Work effectively in inter-disciplinary field with the knowledge of Artificial Intelligence and Machine Learning to develop solutions to the real-world problems.
  2. PEO 2: To communicate and work effectively on team based engineering projects and will practice the ethics of their profession consistent with a sense of social responsibility.
  3. PEO 3: Excel as socially committed engineers or entrepreneurs with high ethical and moral values.
  • PSO-1  Apply fundamental concepts of Data Sciences, Artificial Intelligence and Machine Learning to solve multidisciplinary engineering problems.
  • PSO-2 To communicate and work effectively on team based engineering projects and will practice the ethics of their profession.

Faculty Details

S.NO Faculty Name Designation Qualification UID Profile
1 Ms. MARRI ARSHA HOD B.Tech, MBA 7764-220524-110709 View Profile
2 Mrs.K.ANUSHA Asst.Prof. M.Tech 6641-150418-231038 View Profile
3 Mr.RAVI KUMAR GUMMULA Asst.Prof. M.Tech 7066-190220-174538 View Profile
4 Mr. Arul Asst Prof M.Tech, Ph.D(P) 8073-220609-114644 View Profile
5 Ms.JULME BHAGYASHRI Asst.Prof. M.Tech 3418-230113-091946 View Profile
6 Mrs.JAGRITI KUMARI Asst.Prof. M.Tech 5088-230314-122612 View Profile
Accordion Content

Courses

II B.Tech II Semester
Theory Practical
Computer Organisation Question Bank Computer Organisation  Lab
Database Management Systems Question Bank Database Management Systems Lab
Operating Systems Question Bank Operating Systems Lab
Business Economics and Financial Analysis Question Bank Gender Sensatization Lab
Formal Languages and Automata Theory Question Bank
III B.Tech I Semester
Theory Practical
Design and Analysis of Algorithms Question Bank Design and Analysis Lab
Data Communications and Computer Networks Question Bank Software Engineering Lab
Software Engineering Question Bank Computer Networks LAb
Fundamentals of Management Question Bank
Open Elective-1 PEC Question Bank
Professional Ethics
III B.Tech II Semester
Theory Practical
Compiler Design Question Bank Web Technologies Lab
Web Technologies Question Bank Advanced English Communication Skills Lab
Cryptography and Network Security Question Bank Cryptography and Network Security Lab
Open Elective II Question Bank
Professional Elective  1 Question Bank
IV B.Tech II Semester
Theory Practical
Management Science Question Bank Industry Oriented Mini Project
Adhoc and Sensor Networks(Elective – III) Question Bank Seminar
Semantic Web and Social Networks (Elective – IV) Question Bank Project Work
Comprehensive Viva
Electives
Open Elective   Disaster Management Intellectual Property Rights Human Values and Professional Ethics Elective – I     Software Project Management Image Processing and Pattern Recognition Mobile Computing Computer Graphics Operations Research
Elective – II Machine Learning Soft Computing     Information Retrieval Systems Artificial Intelligence Computer Forensics Elective – III Adhoc and Sensor Networks Storage Area Networks Database Security Embedded Systems
Elective – IV Web Services Semantic Web and Social Networks Scripting Languages Multimedia and Rich Internet Applications Professional  Elective- I Mobile Computing Design patterns Artificial Intelligence Information security Management(Security Analyst1) Introduction to Analytics(Associate Analytics-1)

Syllabus

Events

Academic Excellence

I Year
Academic Year S.No. H.T. No. Name of the Student Branch Section %
2022-23 1 22BK1A72A0 S. Archana AI&DS A 89.68
2 22BK1A7259 K. Viswakarma A 89.49
3 22BK1A7268 M.Ignatius Anto Jennifer A 89.49
2021-22 1 21BK1A7215 GANDI PRIYANKA AI&DS A 90.56
2 21BK1A7207 CHAGANTI SURYANARAYANA MURTHY A 87.89
3 21BK1A7244 POONAM A 87
II Year
Academic Year S.No. H.T. No. Name of the Student Branch Section %
2022-23 1 21BK1A7227 K. S. Hari Kiran Vamshi AI&DS A 87.68
2 21BK1A7207 C. Surya Narayana Murthy A 86.26

Academic Facilities