ADMISSION's

B.Tech ADMISSION

S.NO COURSE INTAKE 2022-23 2023-24 2024-25
01 DATA SCIENCE 66 55 58 66

Lateral (2nd Year)

S.NO COURSE 2022-23 2023-24 2024-25
01 DATA SCIENCE 0 12 15


HOD Of Data Science

Principal

Dr. Nagavelli Ramana

Principal, HOD of CSE,IT,CSD

:9885288905

: ramanauce.ku@gmail.com

Click here to view Profile

Department of Data Science.

Data Science is an interdisciplinary field focused on extracting insights and knowledge from vast amounts of data. Combining principles from mathematics, statistics, computer science, and domain-specific knowledge, data science aims to analyze structured and unstructured data to identify patterns, make predictions, and drive informed decision-making. In a world increasingly reliant on data, data science empowers industries, governments, and individuals to make smarter, evidence-based choices. Key areas within data science include:

• Data Collection and Management: The foundation of data science lies in gathering and storing data efficiently. This involves collecting data from diverse sources, organizing it within databases, and ensuring it’s accessible for analysis.

• Data Analysis and Statistical Modeling: Statistical techniques are used to identify patterns, relationships, and trends within data. By applying statistical models, data scientists gain insights that support decision-making across various domains.

• Machine Learning and Artificial Intelligence (AI): Machine learning enables computers to learn from data, recognizing patterns and making predictions or decisions without explicit programming. This can involve supervised learning (where data with known labels is used), unsupervised learning (discovering hidden patterns in unlabeled data), and reinforcement learning.

• Data Visualization: Visualizing data insights through charts, graphs, and interactive dashboards is crucial for conveying complex findings to stakeholders. Effective data visualization makes insights accessible and actionable, supporting clear communication.

• Big Data and Cloud Computing: With massive data sets generated every day, big data technologies enable the storage, processing, and analysis of large-scale information. Cloud computing plays a significant role in providing scalable infrastructure to handle data science operations.

• Natural Language Processing (NLP): NLP is a branch of data science that focuses on enabling computers to understand and process human language. From chatbots to sentiment analysis, NLP is increasingly critical in handling unstructured data like text and speech.



Faculty of Data Science

Sl.no. Photo Name Qualification Department Mobile No Email Id
01 Dr. Nagavelli Ramana Ph.D CSE 9885288905 ramanauce.ku@gmail.com
02 Makula Vani M.Tech (Ph.D) CSE 8919611798 Makula.vani@gmail.com
03 Dugyala Ramesh M.Tech
Software Engineering		 CSE 9866465488 ramesh1222.cse@gmail.com
04 E.Rajeshwari M.Tech CSE 9985842080 rajeshwarie732@gmail.com
05 V Ramana Babu M.Tech (Ph.D) CSE 9346313635 ramana.vrb@gmail.com
06 Dhatrika BhagyaLaxmi M.Tech (Ph.D) CSE 7330858534 bhagyakmp519@gmail.com
07 MANTHU REKHASREE M.Tech (Ph.D) CSE 8074151879 rekhasreenivasgone@gmail.com
08 Sushmitha Rayabharapu M.Tech (Ph.D) CSE 8341381402 sushmacse511@gmail.com
09 R. Lakshman Naik M.Tech, (Ph.D) IT 9177644143 lakshman.ramavathu@gmail.com
10 Mamidala Soujanya M.Tech, (Ph.D) IT 9010610430 soujanyavedh@gmail.com
11 Damera Priyanka M.Tech, (Ph.D) IT 8106061311 priyankadamera1223@gmail.com


LABS

Computer Lab (PPS) :

The PPS (Programming For Problem Solving) Computer Lab is a state-of-the-art facility designed to foster innovation and hands-on learning. Equipped with high-performance computers, advanced software tools, and high-speed internet connectivity, the lab provides students with an ideal environment for programming, software development, and digital communication projects. Key features:

• Modern Workstations: High-spec computers tailored for coding, simulations, and design.

• Advanced Software: Access to licensed development tools, programming environments, and database applications.

• Collaborative Space: Designed to encourage teamwork and group discussions for project development.

• 24/7 Accessibility: Ensures flexibility for students to work at their convenience.

• Technical Support: Dedicated staff available for assistance and troubleshooting.

Simulation Lab :

The Simulation Lab is an advanced facility designed to provide students with a practical and immersive learning experience. It serves as a bridge between theoretical knowledge and real-world application by offering cutting-edge tools and technology for modeling, analyzing, and simulating complex systems. Key features:

• High-Performance Systems: Equipped with powerful computing resources to handle complex simulations.

• Specialized Software: Access to industry-standard tools for system modeling, simulation, and analysis, including MATLAB, Simulink, and Multisim.

• Real-World Applications: Enables students to simulate and study scenarios in engineering, robotics, communication systems, and more.

• Interactive Environment: Provides a collaborative space for group projects and research initiatives.

CSE & IT Lab :

The CSE (Computer Science and Engineering) & IT (Information Technology) Lab is a dynamic and resourceful space designed to support learning, research, and innovation in the fields of computer science and IT. The lab is fully equipped with advanced tools and technologies to cater to the diverse needs of students and faculty. Key Features:

• Modern Computing Infrastructure: High-performance systems capable of handling programming, machine learning, and data processing tasks.

• Programming Tools: Access to a wide range of compilers, IDEs (Integrated Development Environments), and debugging tools for multiple programming languages.

• Networking & Cybersecurity: Facilities to simulate and analyze networks, along with tools for cybersecurity training and ethical hacking.

• Cloud Computing & Databases: Resources for hands-on experience in database management systems and cloud technologies.