Department of CSE (Data Science)

Transforming Data into Actionable Insights

About the Department

Data Science is an interdisciplinary field that combines statistics, computer science, machine learning, and domain expertise to extract meaningful insights from structured and unstructured data.

The B.Tech. CSE (Data Science) program is a cutting-edge specialization, started in the academic year 2021–2022. The department's curriculum is designed to meet the evolving demands of the data-driven industry, covering advanced topics in big data analytics, predictive modeling, and data visualization.The department is equipped with state-of-the-art infrastructure and modern laboratories that provide hands-on experience with industry-standard tools and technologies. All laboratories maintain a 1:1 student-to-equipment ratio, ensuring optimal learning conditions.

DS Photo

Vision & Mission

Vision

"To create a center of excellence in Data Science education that produces skilled professionals capable of solving complex real-world problems through data-driven decision making."

Mission

  • Provide comprehensive education in data science fundamentals, analytics, and visualization techniques.
  • Foster innovation through industry collaborations and research in emerging areas of data science.
  • Develop ethical data scientists with strong analytical skills and leadership qualities for lifelong learning.

Program Assessment Committee (PAC)

SNO Name Designation Address
1 Dr P Mallikarjuna Reddy Chairman Principal
2 Dr. G Rajesh Chandra Convener HOD, CSE Department
3 Dr. U Vidhya Sagar Member Senior Faculty, CSE Department
4 Dr. K Govardhan Reddy Member Senior Faculty, G Pulla Reddy Engineering College, Kurnool
5 Mr. Rajesh Kumar Member Data Science Lead, Accenture, Bangalore

Program Outcomes (POs), PEOs & PSOs

Program Outcomes (POs)

PO No Graduate Attribute PO Statement
1 Engineering Knowledge Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex Engineering problems.
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.
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.
4 Conduct Investigations of Complex Problems Ability to review research literature, use research methods to execute project and synthesize the problem to provide valid conclusions.
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.
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.
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.
8 Ethics Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9 Individual and team work Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
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.
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.
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.

Program Educational Objectives (PEOs)

PEO No Statement
PEO1 Graduates will be capable of adapting to new technologies and systems, making contributions, and innovating in the key domains of data science.
PEO2 Graduates will be ethically and socially responsible solution providers and entrepreneurs in the field of Computer Science and Engineering with Data Science Specialization.
PEO3 Graduates will be able to successfully pursue higher education in Data Science Specialization.

Program Specific Outcomes (PSOs)

PSO No Statement
PSO1 Build skills to develop software applications in specialized areas of Data Science and Machine Learning.
PSO2 Apply the various Data Science and ML techniques for industrial applications in the areas of Deep Learning, Cloud Computing, Natural Language Processing, and emerging areas.

Board of Studies (BoS)

S.No Name Designation
1 Dr. G Rajesh Chandra BOS Chairman
2 Dr. U Vidhya Sagar University Nominee
3 Dr. Srinivas Reddy Academic Expert
4 Mr. Rajesh Kumar Industry Expert

Programs Offered

B.Tech (CSE) - Data Science

Intake: 60 seats

Academic Regulations: R21, R23, R24

Academic Calendar

UG - B.Tech

  • I-B.Tech I & II Sem
  • II-B.Tech I & II Sem

HOD's Message

"As the head of the Data Science department, I am proud to witness the remarkable growth and achievements of our faculty and students. In this era of big data, our department is committed to nurturing data scientists who can transform raw data into actionable insights that drive innovation and business success."

Our Faculty

S.NO Name Designation Qualification Profile
1 Dr. G RAJESH CHANDRA Professor & HOD M.Tech, Ph.D View
2 Dr. U VIDHYA SAGAR Associate Professor M.Tech, Ph.D View
3 Mr. N MALLIKARJUNA REDDY Assistant Professor M.Tech View
4 Mrs. K MANIKYAMMA Assistant Professor M.Tech(Ph.D) View

CSE (Data Science) Labs

The Department consists of well-equipped laboratories with high-speed internet connectivity. These labs provide hands-on experience with modern data science tools, big data platforms, and analytics software.

Data Analytics Lab-1

40 High-Performance Workstations

Data Analytics Lab-2

40 High-Performance Workstations

Big Data Lab

Hadoop & Spark Cluster Setup

Curriculum Labs:
Python Programming Lab
Statistics & Probability Lab
Data Structures Lab
Database Management Systems Lab
Machine Learning Lab
Data Visualization Lab
Big Data Analytics Lab
Deep Learning Lab
Data Mining Lab
Cloud Computing Lab
Business Intelligence Lab
Time Series Analysis Lab

Research Publications

AY (2023-2024)
  • Dr. G RAJESH CHANDRA, "PREDICTIVE ANALYTICS FOR CUSTOMER CHURN USING MACHINE LEARNING", International Journal of Data Science, Vol 15 Issue 02, 2024.
  • Dr. U VIDHYA SAGAR, "BIG DATA PROCESSING WITH APACHE SPARK: A COMPREHENSIVE STUDY", Journal of Big Data Analytics, Volume 10, Issue 3, March 2024.
  • Mr. N MALLIKARJUNA REDDY, "SENTIMENT ANALYSIS OF SOCIAL MEDIA DATA USING DEEP LEARNING", IEEE Transactions on Data Science, April 2024.
AY (2022-2023)
  • Mrs. K MANIKYAMMA, "DATA VISUALIZATION TECHNIQUES FOR BUSINESS INTELLIGENCE", Journal of Visual Analytics, Jan 2023.
  • Dr. G RAJESH CHANDRA, "REAL-TIME FRAUD DETECTION USING STREAMING DATA ANALYTICS", International Conference on Data Science, June 2023.

NPTEL Achievements

Faculty Particulars

View NPTEL certification details for our faculty members.

Click Here

Student Particulars

View NPTEL certification details for our students.

Click Here

Mentors List

Mentoring Overview

Each mentor is assigned with 15 students. Students are mentored at regular intervals twice in a semester. Parents are informed about attendance and marks via SMS.

10
Mentors
15
Students/Mentor
2/Sem
Frequency
Year Mentor Name Roll Numbers Count
III-CSE(DS) Dr. U VIDHYA SAGAR 21AM1A3201-21AM1A3215 15
II-CSE(DS) Mr. N MALLIKARJUNA REDDY 22AM1A3201-22AM1A3215 15
I-CSE(DS) Mrs. K MANIKYAMMA 23AM1A3201-23AM1A3215 15

Department Events Calendar

Lecture Notes

Year Semester I Semester II
I-YEAR (R23) Python Programming Data Structures
II-YEAR (R21) Statistics for Data Science Click Database Management Systems
III-YEAR (R21) Machine Learning Click Big Data Analytics
IV-YEAR (R21) Deep Learning Click Business Intelligence