

B.Tech in Computer Science and Engineering (Data Science) – Overview
The Bachelor of Technology in Computer Science and Engineering (Data Science) is a four-year undergraduate programme designed to build a strong foundation in computer science while integrating specialized learning in data science, analytics, machine learning, and big data technologies. The course prepares students for careers in data-driven industries, analytics, and software engineering by combining rigorous theory with hands-on experience in real-world applications.
The curriculum balances computing fundamentals with domain knowledge in statistics, data mining, predictive modeling, and data visualization, enabling graduates to extract actionable insights from complex datasets.
Programme Highlights
Combines core computing with practical data science applications
Emphasis on programming, analytics, and data interpretation
Industry-aligned curriculum with labs and project work
Training in modern tools and technologies used in data science
Internship and placement support through the Career Development Cell
Eligibility & Entrance Exam
| Criteria | Details |
|---|---|
| Qualification | Pass in Class 12 from a recognised board |
| Mandatory Subjects | Physics, Mathematics, Chemistry, English |
| Entrance Exams Accepted | JEE Main / CUET-UG |
| Admission Basis | Merit and entrance selection as per university norms |
Admission & Selection Process
| Step | Process |
|---|---|
| 1 | Fill and submit the online application form |
| 2 | Provide entrance exam scores (JEE Main or CUET-UG) |
| 3 | Merit evaluation based on qualifying results and exam score |
| 4 | Offer of admission issued to eligible candidates |
| 5 | Confirm admission by paying requisite fees |
Admission is based on merit and accepted exam scores as per JKLU guidelines.
Academic Fee Structure
| Programme | Duration | Academic Fee per Year |
|---|---|---|
| B.Tech CSE (Data Science) | 4 Years | INR 2,84,000 |
Hostel, mess, and other charges are applicable separately.
Curriculum Overview
The curriculum unfolds across eight semesters and blends core computer science with specialized data science courses.
Core Study Areas
Programming Fundamentals
Data Structures and Algorithms
Database Management Systems
Computer Networks
Software Engineering
Probability and Statistics
Data Mining and Machine Learning
Big Data Technologies
Predictive Modeling
Data Visualization
Capstone Project and Industry Internship
These components ensure a balance between computational skills and data interpretation expertise.
Career Scope
Graduates of B.Tech CSE (Data Science) have diverse career opportunities in the rapidly growing field of data and analytics.
Possible Career Roles Include:
Data Scientist
Data Analyst
Business Intelligence Developer
Machine Learning Engineer
Data Engineer
Analytics Consultant
Database Specialist
Research Associate
This field is relevant across sectors such as finance, healthcare, e-commerce, telecommunications, consulting, and more.
Placements & Internship Support
JKLU’s Placement and Career Development Cell supports students by facilitating internships, industry projects, and placement opportunities. The cell offers training, resume preparation, interview practice, and corporate engagement to maximise employability.
Graduates benefit from the university’s network of recruiters and structured placement efforts.
Why Choose This Programme
Strong combination of computing and data science expertise
Hands-on learning with real data and project assignments
Exposure to modern analytics tools and frameworks
Career-oriented modules aligned with industry expectations
Dedicated placement and career support structure
Programme Summary
The B.Tech in Computer Science and Engineering (Data Science) at JK Lakshmipat University is a forward-looking undergraduate programme designed to meet the growing demand for data professionals. Through a blend of core computer science and specialized data science training, students are prepared to excel in data-centric roles across industries and pursue advanced academic or research paths.
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