Department of CSE- DATA SCIENCE

Vision:

Empowering women graduates as globally competent data scientists, analytical innovators, and ethical researchers through cutting-edge education in data science, enabling them to deliver intelligent, sustainable, and comprehensive solutions to societal challenges through innovation and world-class research.

Mission:

Nurturing a research-driven and industry-integrated academic ecosystem equipped with advanced infrastructure and emerging technologies, empowering women professionals to excel and contribute meaningfully in the data-driven global society.
Equipping students with practical exposure, analytical thinking, and problem-solving abilities through experiential learning, industry engagement, and real-world project-based education.
Promoting interdisciplinary learning, ethical responsibility, and leadership among women, fostering innovation and entrepreneurship to address societal and industrial challenges effectively.

About the Department

The Department of Computer Science and Engineering (Data Science), established in 2020, offers a specialized B.Tech program designed to meet the rapidly evolving demands of the data-driven global ecosystem. The program was initially introduced with an intake of 60 students, and from 2022 onwards, the intake has been enhanced in alignment with increasing industry demand for skilled data science professionals.
Data Science is a transformative and interdisciplinary field within Computer Science and Engineering that integrates statistics, mathematics, and computational techniques to extract actionable insights from complex and large-scale data. The discipline spans the complete data lifecycle, including data acquisition, preprocessing, analysis, visualization, management, and knowledge discovery, thereby enabling intelligent decision-making and fostering innovation across domains.
To promote innovation, research, and entrepreneurship, the department has established a Centre of Excellence (CoE) focusing on emerging technologies, patents, and consultancy activities. Furthermore, a Technology Business Incubator (TBI) provides a nurturing platform for startups and student-driven innovations, enabling the transformation of ideas into impactful products and solutions.

The goals of the department are to:

To develop strong theoretical foundations and practical proficiency in core and emerging areas such as Essentials of Data Science with R, Statistical Foundations of Data Science, Data Handling and Visualization, Data Engineering, Big Data Analytics, Machine Learning, Artificial Intelligence, Business Analytics, Data Science Tools and Techniques, and Full Stack Development.
To cultivate analytical thinking, problem-solving capabilities, and data-driven decision-making skills required to address real-world challenges.
To provide a supportive, inclusive, and flexible learning environment, accommodating diverse student backgrounds, aspirations, and learning needs.
To enable hands-on learning experiences through industry-relevant tools, programming languages such as Python and R, data engineering practices, and modern big data platforms.
To promote real-time projects, research, innovation, and lifelong learning, supported by internships, interdisciplinary collaborations, and industry engagement.

CAREER OPPORTUNITIES AFTER COMPLETION OF THE COURSE :

Graduates of the B.Tech program in Computer Science and Engineering (Data Science) are equipped with strong analytical, technical, and problem-solving skills, enabling them to pursue diverse and rewarding career paths across industries such as IT, healthcare, finance, e-commerce, manufacturing, and consulting.
The prominent career opportunities include:
Data Scientist – Designing predictive models, extracting insights, and solving complex business problems using advanced analytics and machine learning techniques.
Data Analyst – Interpreting data, generating reports, and supporting data-driven decision-making processes within organizations.
Data Engineer – Building and managing data pipelines, ensuring efficient data collection, storage, and processing for large-scale systems.
Machine Learning Engineer – Developing, deploying, and optimizing machine learning models for real-world applications
Artificial Intelligence Engineer – Creating intelligent systems using AI techniques such as deep learning, natural language processing, and computer vision.

Programmable Educational Objectives - PEOs

PEO1 - Professional Excellence:

Graduates will attain strong foundational knowledge in mathematics, statistics, computer science, and data science to design and develop intelligent, sustainable, and efficient solutions for complex real-world problems.

PEO2 - Research and Innovation Orientation

Graduates will exhibit analytical thinking, creativity, and research aptitude to explore emerging technologies, drive innovation, and contribute to advancements in data science and allied disciplines.

PEO3 - Employability and Entrepreneurial Competence

Graduates will develop technical, managerial, and entrepreneurial skills enabling them to excel in professional careers, higher education, or startup ventures in the field of data science

PEO4 - Ethical and Societal Responsibility

Graduates will demonstrate professional ethics, leadership qualities, and social responsibility in applying data-driven solutions for the betterment of society and the environment.

PEO5 - Lifelong Learning and Global Adaptability

Graduates will pursue continuous learning and professional development to adapt to evolving technologies, global standards, and interdisciplinary domains in data science.

Program Outcomes

PO1

Engineering knowledge

Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.

PO2

Problem analysis

Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)

PO3

Design / development of solutions

Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)

PO4

Conduct investigations of complex problems

: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8).

PO5

Engineering Tool Usage

Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)

PO6

The Engineer and The World

Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7).

PO7

Ethics

Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8

Individual and Collaborative Team work

Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.

PO9

Communication

Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences

PO10

Project Management and Finance

Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.

PO11

Life-Long Learning

Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Program Specific Outcomes - PSOs

PSO1

Graduates will be able to integrate data acquisition, statistical modeling, and machine learning techniques to analyze complex datasets, extract actionable insights, and design intelligent, data-driven solutions that effectively address real-world challenges in healthcare, education, agriculture, environment, smart systems, and other multidisciplinary domains.

PSO2

Graduates will demonstrate technical proficiency, innovative thinking, and research orientation in designing and implementing data-centric systems and software applications, while maintaining professional ethics, leadership, and social responsibility through industry engagement, experiential learning, and lifelong adaptability to emerging technologies.

EAPCET/ICET CODE: MRCW