120
Intake
Department Identity
Known for
A practical analytics culture covering data engineering basics, model building, visualization, and business-facing decision support.
Students here become
Data professionals who can clean data, model outcomes, present insights, and ship dashboard-backed solutions.
- Outcome
Strong blend of statistics, programming, and domain interpretation
- Outcome
Project evaluations prioritize reproducibility and measurable outcomes
- Outcome
Continuous exposure to real datasets and reporting workflows
Vision & Mission
Vision
To build an academically strong, industry-aware, and ethically grounded department that prepares students for technical careers, higher studies, and responsible professional life.
Mission
- Data analysis and statistical reasoning
- Python, R, and analytics workflow practice
- Big data tools, dashboards, and forecasting
POs, PEOs, PSOs
PEOs set the graduate vision, POs define the standard, and PSOs show the department specific skills.
PEO
3
PO
12
PSO
2
PEO
Program Educational Objectives
PEO 1
Graduates will use data-driven methods to solve problems across analytics, AI, and decision-support domains.
PEO 2
Graduates will continue professional growth through higher studies, certifications, and ethical practice.
PEO 3
Graduates will adapt to evolving data technologies and contribute to research or entrepreneurial initiatives.
PO
Program Outcomes
Engineering Knowledge
Apply mathematics, science, engineering fundamentals, and specialization knowledge to solve complex problems.
Problem analysis
Identify, formulate, review research literature, and analyze complex engineering problems using first principles.
Design/development of solutions
Design solutions with consideration for public health, safety, culture, society, and environment.
Conduct investigations of complex problems
Use research-based knowledge and methods to synthesize valid conclusions.
Modern tool usage
Apply modern tools for prediction, modeling, and analysis with awareness of limitations.
The engineer and society
Assess societal, health, safety, legal, and cultural responsibilities relevant to practice.
Environment and sustainability
Understand the impact of engineering solutions in societal and environmental contexts.
Ethics
Apply ethical principles and professional responsibilities.
Individual and team work
Function effectively in diverse teams and multidisciplinary settings.
Communication
Communicate effectively through reports, presentations, and instructions.
Project management and finance
Demonstrate knowledge of engineering and management principles in project environments.
Life-long learning
Engage in independent and life-long learning in the context of technological change.
PSO
Program Specific Outcomes
PSO 1
Apply programming and mathematical concepts to develop scalable data science solutions.
PSO 2
Demonstrate proficiency in analytics tools and technologies to build intelligent systems and pursue careers in industry, research, or higher education.
Programs offered
B.Tech Data Science
Duration: 4 Years
Intake: 120
HOD
Dr. Nagarama Devi
Head of the Department, CSE (DS)
Qualification: Ph.D. in related field
Experience: 18 years of combined teaching and industry experience.
Phone: +91-92463-23444
From The HOD's Desk
“The department promotes data literacy, evidence-based thinking, and practical analytics.”
Staff
View the full faculty and staff directory for department-level contacts, academic profiles, and support details.
Open faculty & staff directoryCourse Structure
B.Tech Data Science
4 Years • Intake 120
Syllabus PDFs
Department Associations
Data challenge workshops
Visualization competitions
Seminars on business intelligence and AI
Infrastructure
Data Visualization Lab
Tools: Advanced computing tools and hardware
Available during college hours
Python and Analytics Studio
Tools: Advanced computing tools and hardware
Available during college hours
Database and Reporting Lab
Tools: Advanced computing tools and hardware
Available during college hours
Project collaboration corner
Tools: Advanced computing tools and hardware
Available during college hours
Department Events
Data challenge workshops
Visualization competitions
Seminars on business intelligence and AI
Innovative Teaching Methodologies
Project-led classes with task-based exercises and reviewable outputs
Layered evaluation across labs, presentations, and written analysis
Mentor reviews by faculty and external experts
Student Projects
Case studies based on datasets and dashboards
Published / Developed internal tool
Research notes on analytics and prediction
Published / Developed internal tool
Student poster presentations and seminar papers
Published / Developed internal tool
Student Achievements
Student achievements
CSE (Data Science) student achievements
Department Placements
Highest
18 LPA
Average
4.9 LPA
Median
4.2 LPA
Top recruiters for this department
Department magazines
Newsletter
Data Lens Digest Magazine
Current
Academic Year
Feature stories, project showcases, and campus voices.
Open PDFDepartment clubs
Data Science Club
Analytics Challenge Team
Data Storytelling Series
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Share feedback about the department experience, student support, and academic environment.
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Department contact
Department Office - CSE (Data Science)
Department Office
Reach out
Email: info@sreyas.ac.in
Phone: +91-92463-23444