BS Data Science & Business Analytics
Program Overview
The BS in Data Science & Business Analytics at NIT is designed for students who want to turn data into decisions and insight into impact. Developed using Arizona State University’s (ASU) curriculum, the program prepares graduates to work at the intersection of technology, analytics, and business strategy in data-driven organizations.
Built on a strong foundation in programming, data structures, mathematics, statistics, and computational thinking, the curriculum emphasizes analytical rigor, problem framing, and evidence-based decision-making. Students learn how data is collected, processed, modeled, and translated into actionable business intelligence.
The program integrates advanced domains such as machine learning, big data, business intelligence, artificial intelligence, and enterprise analytics, ensuring graduates are prepared for rapidly evolving analytical roles. A strong focus on ethics, sustainability, behavioral dynamics, and innovation develops responsible professionals who can lead data-driven transformation.
Students gain hands-on experience through labs, professional internships, and a final-year capstone project focused on real organizational challenges. Applied coursework in data visualization, statistical modeling, and analytics platforms ensures graduates are both technically capable and business-ready.
Graduates of the BS in Data Science & Business Analytics are equipped for high-impact roles across finance, marketing, supply chain, technology, and consulting, as well as for postgraduate study or entrepreneurial ventures in analytics-led fields.
Dual Degree Pathway (3+1 Program)​
The BS in Data Science & Business Analytics offers a 3+1 Dual Degree Pathway in partnership with Arizona State University (ASU) through The College of Liberal Arts and Sciences. Students may complete all four years at NIT or choose the 3+1 option studying three years at NIT and the final year at Arizona State University, either online or on-campus.
Upon successful completion, students earn two internationally recognized degrees:
- A Bachelor’s in Data Science & Business Analytics from the National Institute of Technology (NIT), and
- A B.S. in Data Science from Arizona State University (ASU)
This dual-degree structure provides strong academic depth, international exposure, and global recognition, positioning graduates for careers at the intersection of data, technology, and strategic decision-making. Final-year progression and dual-degree eligibility are subject to successful credit transfer and Arizona State University approval.
Career Pathways:
Graduates of the BS in Data Science and Business Analytics (3+1) are prepared for high-impact roles where data, technology, and business strategy intersect. The program equips students to work across technical, analytical, and decision-making functions in diverse industries.
- Data ScientistÂ
- Machine Learning EngineerÂ
- Business Intelligence AnalystÂ
- Data AnalystÂ
- AI SpecialistÂ
- Big Data EngineerÂ
- Business Analytics ManagerÂ
- Enterprise Data ArchitectÂ
- Financial Data AnalystÂ
- Marketing Data AnalystÂ
- Supply Chain Data AnalystÂ
- IT Business AnalystÂ
- Innovation ConsultantÂ
- Technology Strategist
NIT Admission Criteria:
The National Institute of Technology (NIT) seeks to admit academically prepared, motivated, and intellectually curious students who demonstrate the potential to contribute positively to the university’s learning environment and to society. Meeting the minimum eligibility requirements qualifies an applicant for admission evaluation but does not guarantee admission. Applicants may apply if they meet any one of the minimum criteria outlined below:
- Matriculation/Intermediate Requirements:
- 12 years of formal education with a minimum of 60% marks (no specific subject requirements).  Â
- Cambridge International (O & A Levels):
- O Level: Eight subjects (English, Mathematics, Urdu, Islamiat, Pakistan Studies + 3 electives), with an average of grade C. (Additional Mathematics does not count as an elective)
- A Level: Three principal subjects with an average of grade C. (Further Mathematics and General Paper are excluded.)
- International Baccalaureate (IB):
- Minimum 30/45 points.  Â
- English is compulsory; CAS and TOK must be completed.  Â
- Students must also pass Urdu, Islamiat and Pakistan Studies (via O-Level/SSC/IB).
- High School Diploma (HSD):
- Minimum 60% overall.  Â
- English is required, along with four principal electives in grades 9–12. Â
- Students must also pass Urdu, Islamiat and Pakistan Studies (via O-Level/SSC/HSD)Â
ASU Admission Criteria:
Minimum transfer Grade Point Average (GPA): Transfer students must have a minimum 2.5 cumulative transfer GPA (with a 3.00 GPA in core competency coursework (4.00 = “A”).Â
Proof of English proficiency: 79 iBT TOEFL; 6.5 IELTS; PTE 58; Duolingo 105 or equivalent; Global Launch’s online English for Undergraduate Admission or full-time English Language Program (campus or online immersion).
Fee Structure For The Academic Year 2025-26 (PKR)
One-time Admission Fee: 145,000
One-time Security Fee: 50,000
Semester Registration Fee: 40,000 per semester
Tuition Fee:
Fall semester: 547,500
Spring semester: 657,000
Total tuition fee for the Academic year 2025-26: 1,479,500
Program Plan
Year One
| Spring Semester 1 | Credits |
|---|---|
PSE 100: Introduction to Engineering | 3 Credits |
CSE 110: Principles of Programming | 3 Credits |
MAT 265: Calculus for Engineers 1 | 3 Credits |
CEE 181: Technological, Social, & Sustainable System | 3 Credits |
PHI 105: Intro to Ethics | 3 Credits |
| Total Credits | 15 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
CSE 205: Object-Oriented Programming and Data Structures | 3 Credits |
MAT 266: Calculus for Engineers II | 3 Credits |
CHM 107: Chemistry and Society | 3 Credits |
CHM 108: Chemistry and Society Laboratory | 3 Credits |
EEL 120: Digital Design Fundamentals | 3 Credits |
MGT 302: Principles of International Business | 3 Credits |
PAK 101: Islamic Studies | 3 Credits |
| Total Credits | 21 Credits |
Year Two
| Spring Semester 1 | Credits |
|---|---|
ENG 101: English Composition 1 | 3 Credits |
CSE 240: Introduction to Programming Languages | 3 Credits |
MAT 263: Discrete Mathematical Structures | 3 Credits |
PHY 221: Calculus for Engineers III | 3 Credits |
PHY 131: University Physics II: Electricity and Magnetism | 3 Credits |
| PHY 132: University Physics Laboratory II | 3 Credits |
| PAK 102: History and Culture of Pakistan | 3 Credits |
| Total Credits | 21 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
ENG 102: English Composition II | 3 Credits |
CSE 230: Computer Organization and Assembly Language Programming | 3 Credits |
CSE 310: Data Structures and Algorithms | 3 Credits |
FIS 201: Innovation in Society | 3 Credits |
PHY 131: University Physics II: Electricity and Magnetism | 3 Credits |
PHY 132: University Physics Laboratory II | 3 Credits |
| Total Credits | 18 Credits |
Year Three
| Spring Semester 1 | Credits |
|---|---|
CSE 355: Introduction to Theoretical Computer Science | 3 Credits |
CSE 301: Computing Ethics | 3 Credits |
CSE 360: Introduction to Software Engineering | 3 Credits |
CSE 365: Information Assurance | 3 Credits |
IEE 380: Probability and statistics for Engineering Problem Solving | 3 Credits |
PSY 101: Introduction to Psychology | 3 Credits |
| Total Credits | 21 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
CSE 345: Principles of Programming Languages | 3 Credits |
CSE 330: Operating Systems | 3 Credits |
CSE 445: Distributed Software Development | 3 Credits |
CSE 455: Database Management | 3 Credits |
MAT 343: Applied Linear Algebra | 3 Credits |
COM 225: Public Speaking | |
CSE 412: Database Management | 3 Credits |
| Total Credits | 18 Credits |
Year Four
| Spring Semester 1 | Credits |
|---|---|
CSE 498: Computer Science Capstone Project I | 3 Credits |
CSE 420: Computer Architecture I | 3 Credits |
CSE 434: Computer Networks | 3 Credits |
CSE 478: Foundation of Data Visualization | 3 Credits |
Elective | 3 Credits |
| Total Credits | 21 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
| CSE 498: Computer Science Capstone Project II | 3 Credits |
| CSE 469: Introduction to Human-Computer Interaction | 3 Credits |
| CSE 471: Introduction to Artificial Intelligence | 3 Credits |
| Elective | 3 Credits |
| Elective | 3 Credits |
| Electives: MGT 380: Management and Strategy CSE 407: Digital Signal Processing CSE 476: Introduction to Natural Language Processing CSE 565: Software Verification, Validation, and Testing CSE 566: Software Project, Process, and Quality Management CSE 543: Information Assurance and Security | 3 Credits |
| Total Credits | 18 Credits |