SVCE Bengaluru
SVCE Bengaluru
SRI VENKATESHWARA COLLEGE OF ENGINEERING AUTONOMOUS, BENGALURU
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COMPUTER SCIENCE AND ENGINEERING - DATA SCIENCE

Overview

The CSE specialization in Data Science equips students with the skills to analyze, interpret, and utilize data for impactful decision-making. It emphasizes both theoretical foundations and practical applications in emerging technologies. Students gain expertise in Machine Learning, AI, Big Data, and Analytics, preparing them for diverse career opportunities. The program fosters problem-solving, teamwork, and innovation through projects and industry collaborations. Graduates are well-prepared for roles like Data Scientist, ML Engineer, and Data Analyst in top industries.




Program Highlights




Why Choose Us?




Career Opportunities

Graduates of this program are in high demand across sectors such as:




To be a centre of excellence in Data Science, empowering professionals to leverage data for ethical, intelligent, and sustainable innovations that transform society and address global challenges.

Mission 1
Deliver cutting-edge education in Data Science, developing globally competent leaders equipped for complex technological and societal challenges.

Mission 2
Advance interdisciplinary research in emerging technologies to create innovative, real-world solutions addressing industry, societal, and global problems.

Mission 3
Foster strong partnerships with industry and global institutions to enhance innovation, entrepreneurship, professional skills, and employability.

Mission 4
Promote ethical, socially responsible, and sustainable data practices that positively impact society and the environment.

Mission 5
Encourage continuous learning, adaptability, and mastery of emerging technologies to prepare leaders for a dynamic global landscape.

Knowledge
CSE- Data Science and Engineering Graduates will have professional technical career in inter disciplinary domains providing innovative and sustainable solutions using modern tools.

Skills
CSE- Data Science and Engineering Graduates will have effective communication, leadership, team building, problem solving, decision making and creative skills.

Attitude
CSE- Data Science and Engineering Graduates will practice ethical responsibilities towards their peers, employers and society.

PSO 1
Ability to adopt quickly for any domain, interact with diverse group of individuals and be an entrepreneur in a societal and global setting.

PSO 2
Ability to visualize the operations of existing and future software Applications.

Engineering Knowledge:
Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

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.

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.

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.

Engineering 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.

The Engineer and The World:
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.

Ethics:
Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

Individual and Collaborative Team Work:
Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

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.

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.

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.

2nd Year 3rd Year 4th Year
3rd SEMESTER
Core Subjects 1. Mathematics for Computer Science
2. Digital Design & Computer Organization
3. Operating Systems
4. Data Structures and Application
5. Data Structures Lab
ESC/ETC/PLC 1. Object Oriented Programming with Java
2. Data Analytics with R
Social Connect and Responsibility
Ability/Skill Enhancement Course 1. Data Analytics with Excel
2. Project Management with Git
Mandatory (Non Credit) National Service Scheme (NSS)
Physical Education (PE) (Sports and Athletics)
Yoga
4th SEMESTER
Core Subjects 1. Analysis & Design of Algorithms
2. Microcontrollers
3. Database Management Systems
4. Analysis & Design of Algorithms Lab
5. Biology For Computer Engineers
6. Universal Human Values course
ESC/ETC/PLC 1. Discrete Mathematical Structures
2. Algorithmic Game Theory
Ability/Skill Enhancement Course 1. Scala
2. MongoDB
Mandatory (Non Credit) National Service Scheme (NSS)
Physical Education (PE) (Sports and Athletics)
Yoga
5th SEMESTER
Core Subjects 1. Software Engineering & Project Management
2. Computer Networks
3. Theory of Computation
4. Data Visualization Lab
5. Mini Project
Ability EnhancementResearch Methodology and IPR
HSMSEnvironmental Studies and E-waste Management
Professional Elective Course 1. Computer Vision
2. Data Warehousing
3. NoSQL Databases
4. Distributed Systems
Mandatory (Non Credit) National Service Scheme (NSS)
Physical Education (PE) (Sports and Athletics)
Yoga
6th SEMESTER
Core Subjects 1. Big Data Analytics
2. Artificial Intelligence & Machine Learning
3. Project Phase I
4. Machine Learning Lab
Professional Elective Course 1. Blockchain Technology
2. Exploratory Data Analysis
Ability/Skill Enhancement Course 1. Generative AI
2. Mobile Application Development with Flutter
Open Elective Course 1. Introduction to Artificial Intelligence
2. Mobile Application Development
Mandatory (Non Credit) National Service Scheme (NSS)
Physical Education (PE) (Sports and Athletics)
Yoga
Indian Knowledge System
7th SEMESTER
Core Subjects 1. Parallel Programming
2. Statistical Machine Learning for Data Science
3. Cryptography & Network Security
Professional Elective Course 1. Scalable Data Systems
2. Business Analytics
3. Data Engineering & MLOps
4. Deep Learning
ProjectMajor Project Phase-II
Open Elective Course 1. Introduction to DBMS
2. Software Engineering
3. Introduction to Algorithms
8th SEMESTER
Core Subjects Internship (Industry/Research) (14 – 20 weeks)
Professional Elective Course BOS will publish courses based on the availability (online)
Open Elective Course BOS will publish courses based on the availability (online)

Our Data Science research team is at the forefront of innovation, dedicated to uncovering advanced methodologies and cutting-edge solutions in the rapidly evolving world of data analytics and artificial intelligence. We focus on tackling complex challenges in data analysis, predictive modelling, and intelligent decision-making to enable transformative applications across diverse industries such as finance, healthcare, and smart cities.

Our team of multidisciplinary researchers, industry professionals, and academic experts collaborates on a range of projects aimed at extracting meaningful insights from complex data sets, improving algorithmic efficiency, and advancing the boundaries of machine learning and big data technologies. By pushing the limits of data science, we contribute to the development of intelligent systems that drive innovation and shape the future of technology.

Key Research Areas

1. Predictive Analytics and Machine Learning

  • Investigating advanced machine learning techniques to predict outcomes and trends in areas like healthcare, finance, and customer behavior.
  • Enhancing model interpretability and reliability through the development of novel algorithms.

    • 2. Natural Language Processing (NLP)

  • Exploring state-of-the-art methods for text analysis, sentiment detection, and language modelling.
  • Researching deep learning models for tasks like machine translation and chatbots.

    • 3. Big Data and Scalable Computing

  • Designing systems and frameworks for handling massive datasets in real-time environments.
  • Researching distributed computing solutions and cloud-based architectures for efficient data processing.

    • 4. Artificial Intelligence in Smart Cities

  • Developing AI-based models to optimize traffic management, energy utilization, and public safety.
  • Researching real-time data integration for intelligent urban planning and resource management.

    • 5. Data Privacy and Security

  • Investigating privacy-preserving techniques for secure data sharing and processing.
  • Developing cryptographic solutions to protect sensitive data while enabling robust analytics.

    • 6. Explainable and Ethical AI

  • Designing frameworks for creating transparent and fair AI models.
  • Conducting research on the ethical implications of AI, ensuring that technologies align with societal values.

    • Our Impact
    Our research has led to significant advancements in the fields of machine learning, big data analytics, and artificial intelligence, influencing academic research and industry practices globally. With publications in leading journals and presentations at premier conferences, our work is recognized as a major contributor to the growth of data science as a discipline. We collaborate extensively with industry partners, government agencies, and academic institutions to ensure our research addresses real-world challenges and drives impactful, tangible solutions.

    Collaborate With US
    We welcome collaboration from researchers, industry professionals, and organizations looking to leverage data science to solve complex problems. By working together, we can lead the next wave of innovation and create intelligent systems that benefit society at large. Reach out to explore opportunities to collaborate and shape the future of data science.



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    Faculty

    Dr. Santosh Kumar S - Associate Professor & Head of the dept
    Dr. SAMPATHKUMAR A - Associate Professor
    Dr. R VELUMANI - Associate Professor
    Mrs. ANBULAKSHMI S - Assistant Professor
    Mrs. ANBULAKSHMI S - Assistant Professor
    Mrs. ANBULAKSHMI S - Assistant Professor