NIET, Greater Noida

B.Tech in Computer Science and Engineering (Data Science)

Noida Institute of Engineering and Technology (NIET), Greater Noida

The Bachelor of Technology (B.Tech) in Computer Science and Engineering (Data Science) at Noida Institute of Engineering and Technology (NIET), Greater Noida is a future-focused undergraduate program designed to equip students with strong analytical, computational, and problem-solving skills required to extract meaningful insights from large volumes of data. The program integrates core computer science concepts with advanced data science, analytics, and machine learning techniques to meet evolving industry demands.

Program Overview

• Degree Awarded: Bachelor of Technology (B.Tech)

• Discipline: Computer Science and Engineering (Data Science)

• Duration: 4 Years (8 Semesters)

• Mode of Study: Full-Time

• Affiliation: Dr. A.P.J. Abdul Kalam Technical University (AKTU)

• Approval: AICTE

• Accreditation: NAAC ‘A’ Grade (Institutional)

• Location: Greater Noida, Uttar Pradesh

Why Choose CSE (Data Science) at NIET?

• Autonomous and industry-relevant curriculum aligned with data-driven technologies

• Strong emphasis on practical learning, analytics, and real-world datasets

• Advanced laboratories for data science, AI, and big data technologies

• Faculty with academic excellence and industry exposure

• Hands-on projects, internships, and live industry assignments

• Dedicated Career Management Centre for placement readiness

Curriculum Highlights

The program offers a balanced blend of theory and application, covering:

• Programming in Python, R, and Java

• Data Structures and Algorithms

• Database Management Systems

• Probability and Statistics for Data Science

• Data Mining and Warehousing

• Machine Learning Fundamentals

• Big Data Analytics

• Data Visualization Techniques

• Artificial Intelligence Basics

• Cloud Computing for Data Analytics

• Business Intelligence and Decision Analytics

• Ethics, Privacy, and Data Security

Students undertake industrial training, minor projects, and a final-year capstone project to gain real-world exposure.

Laboratories & Practical Exposure

Students gain hands-on experience through well-equipped laboratories, including:

• Data Science & Analytics Lab

• Big Data & Hadoop Lab

• Machine Learning Lab

• Data Visualization Lab

• Cloud & Analytics Lab

Eligibility Criteria

• Passed 10+2 or equivalent with Physics and Mathematics as compulsory subjects

• Minimum 45% aggregate marks (40% for SC/ST candidates)

• Admission through JEE Main / state-level counseling or institute-level selection as per norms

Admission Process

• Application through online or offline mode

• Selection based on academic merit and entrance examination scores

• Counseling, seat allotment, and document verification

• Final admission confirmation upon fee submission

Career Opportunities

Graduates of B.Tech in CSE (Data Science) can pursue roles such as:

• Data Scientist

• Data Analyst

• Machine Learning Engineer

• Business Intelligence Analyst

• Big Data Engineer

• Data Engineer

• Analytics Consultant

• AI & Data Research Associate

Placements & Industry Exposure

NIET provides strong placement support through its Career Management Centre, offering:

• Skill-based training and analytics certifications

• Industry internships and live projects

• Resume building, aptitude training, and interview preparation

• On-campus recruitment by leading organizations

Top Recruiters

Amazon, Google, Microsoft, IBM, Accenture, Deloitte, TCS, Infosys, Wipro, Capgemini, Cognizant, Oracle, and other leading analytics-driven companies.

Higher Education & Career Advancement

Graduates may pursue:

• M.Tech / MS in Data Science, AI, or Analytics

• MBA in Business Analytics or Technology Management

• Research and doctoral programs

• Competitive examinations such as GATE

Scholarships

Eligible students may avail:

• Merit-based scholarships

• Government and state scholarship schemes

• Need-based financial assistance

Scholarships are awarded as per institutional and regulatory guidelines.

Infrastructure & Student Life

• Smart classrooms with modern IT infrastructure

• Central library with data science and analytics resources

• Hostel facilities for boys and girls

• Technical clubs, coding communities, and innovation cells

• Academic mentoring and career counseling