BS Artificial Intelligence
Program Overview
The BS in Artificial Intelligence at NIT is designed for students who want to build intelligent systems that learn, reason, and support decision-making at scale. Developed using Arizona State University’s (ASU) curriculum, the program prepares graduates to work at the forefront of AI-driven technologies, data-centric systems, and intelligent automation.
Course Curriculum
Built on a strong foundation in programming, mathematics, statistics, and core computer science, the curriculum emphasizes algorithmic thinking, computational modeling, and responsible AI design. Students progress from foundational computing concepts into advanced areas such as machine learning, deep learning, natural language processing, computer vision, and intelligent systems.
The program balances theory and application, enabling students to design, train, evaluate, and deploy AI models that address real-world problems across industries. Strong emphasis is placed on ethical awareness, governance, and principled innovation, ensuring graduates understand not only what AI can do, but how it should be applied responsibly.
Hands-on learning is central to the program. Through labs, applied projects, structured internships, and a final-year capstone, students gain experience building AI-powered solutions for practical use cases. This ensures graduates are both technically capable and industry-ready.
Graduates of the BS in Artificial Intelligence are equipped for roles across intelligent systems development, data science, automation, and AI research, as well as for postgraduate study or innovation-led entrepreneurial ventures.
Practical Learning Experience
With a strong emphasis on real-world applications, the program includes capstone projects, hands-on labs, and electives in machine learning, digital signal processing, human-computer interaction, and more—ensuring students graduate job-ready and innovation-driven.Â
Note: Final year at ASU and dual degree eligibility depend on successful credit transfer and approval by Arizona State University. Program details may vary based on academic progress.
4+1 Pathway – Bachelor’s + Master’s Degree​
Earn Your Bachelor’s + Master’s in 5 Years.
The BS in Management Science offers a 4+1 Master’s Pathway with Thunderbird School of Global Management at Arizona State University (ASU)
This pathway allows students to complete four years of undergraduate study at NIT, followed by one year at ASU, earning both a bachelor’s and a master’s degree in just five years. *
High-performing students on the 4+1 pathway may choose between two ASU master’s options:
- Master of Global Management (MGM) – On-Campus
A degree at the intersection of Global Business, Public Policy and International Affairs. The MGM is regarded as the most innovative leadership and entrepreneurship degree for professionals seeking a career in top global organizations who are disrupting “business as usual” by redefining or creating entirely new industries. - Master of Leadership and Management (MLM) – Online
Designed to deliver mastery in 21st-century leadership and management principles and practices, preparing leaders to take on additional managerial responsibilities in global organizations or to make a career change across industries or sectors. Courses span the gamut of Thunderbird’s online offerings, from accounting and data-driven decision-making to global finance and marketing.
How It Works
Years 1–4 – At NIT
Complete your bachelor’s degree locally with an ASU-integrated curriculum.
Year 5 – At Arizona State University (Online or On-Campus)
Earn your master’s degree directly from ASU in just one additional year.
OPT Visa
Students choosing to study on campus at ASU may apply for OPT, allowing eligible graduates the opportunity to work legally in the United States for up to three years (depending on program eligibility).
Upon successful completion of the 4+1 pathway, you graduate with:
- Bachelor of Science in Management Science from National Institute of Technology, Pakistan
- Option 1: Master of Global Management (MGM) from Thunderbird School of Global Management at Arizona State University, United States
- Option 2: Master of Leadership Management (MLM) from Thunderbird School of Global Management at Arizona State University, United States*Program details may vary based on academic progress and successful credit transfer and approval by each university. Students participating in the 4+1 pathway must work with their program director at AUT to ensure that credits earned at ASU meet degree requirements at AUT.
*Program details may vary based on academic progress and successful credit transfer and approval by each university. Students participating in the 4+1 pathway must work with their program director at AUT to ensure that credits earned at ASU meet degree requirements at AUT.
Career Pathways:
Graduates of the BS in Artificial Intelligence are prepared for roles at the intersection of data, computation, and intelligent automation. The program develops strong analytical reasoning, algorithmic thinking, and ethical awareness in AI system development.
- Artificial Intelligence Engineer
- Machine Learning Engineer
- Data Scientist
- Computer Vision Engineer
- Natural Language Processing Specialist
- AI Research Assistant
- Robotics & Intelligent Systems Engineer
- Intelligent Automation Engineer
- AI Product Analyst
- Decision Systems Analyst
Graduates may also pursue advanced degrees, research careers, or innovation-led startups in AI and emerging technologies.
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 50% marks (no specific subject requirements).
- 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 24/45 points.
- English is compulsory; CAS and TOK must be completed.
- Students must also pass Urdu, Islamiat and Pakistan Studies (via O-Level/SSC/IB).
- High School Diploma (HSD):
- Minimum 60% overall.
- English is required, along with four principal electives in grades 9–12.
- Students must also pass Urdu, Islamiat and Pakistan Studies (via O-Level/SSC/HSD)
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 |
|---|---|
CSE 110: Principles of Programming | 4 Credits |
MAT 265 / MAT 170: Calculus for Engineers I | 3 Credits |
PHI 105/SSC 101: Islamic Studies | 2 Credits |
SSC 102: Pakistan Studies | 2 Credits |
FSE 100: Introduction to Engineering | 2 Credits |
SSC 100: Fundamentals of Academic Writing | 3 Credits |
| Total Credits | 16 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
CSE 205: Object-Oriented Programming and Data Structures | 4 Credits |
Understanding of Quran 1 | 1 Credits |
MAT 266 / MAT 265: Calculus for Engineers II | 3 Credits |
Civics and Community Engagement | 2 Credits |
EEE 120: Digital Design Fundamentals | 4 Credits |
PHY 121: University Physics I: Mechanics | 3 Credits |
PHY 122: University Physics I Lab | 1 Credits |
| Total Credits | 18 Credits |
Year Two
| Spring Semester 1 | Credits |
|---|---|
COM 225: Public Speaking and Presentations | 3 Credits |
QUR 101: Understanding of Quran || | 1 Credits |
CSE 240: Introduction to Programming Languages | 4 Credits |
MAT 243: Discrete Mathematical Structures | 3 Credits |
DAT 250: Data Science and Society | 3 Credits |
PSY 101: Introduction to Psychology (SOBE) | 3 Credits |
| Total Credits | 17 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
FIS 201: Innovation in Society (HUAD) | 3 Credits |
CEE 181: Technological, Social, and Sustainable Systems | 3 Credits |
CSE 230: Computer Organization and Assembly Language Programming | 4 Credits |
CSE 310: Data Structures and Algorithms | 4 Credits |
IEE 380: Probability and Statistics for Engineering Problem Solving | 3 Credits |
| Total Credits | 17 Credits |
Year Three
| Spring Semester 1 | Credits |
|---|---|
Ideology and Constitution of Pakistan | 2 Credits |
CSE 340: Principles of Programming Languages | 3 Credits |
CSE 331: Computing Ethics | 1 Credits |
Programming for AI | 4 Credits |
Machine Learning | 4 Credits |
Knowledge Representation and Reasoning | 3 Credits |
| Total Credits | 17 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
Elective 1 | 3 Credits |
CSE 445: Distributed Software Development/Parallel & Distributed Computing | 4 Credits |
CSE 412: Database Management | 4 Credits |
MAT 343: Applied Linear Algebra | 3 Credits |
Computer Vision | 3 Credits |
| Total Credits | 17 Credits |
Year Four
| Spring Semester 1 | Credits |
|---|---|
Artificial Intelligence Capstone Project I | 3 Credits |
Elective 2 | 3 Credits |
CSE 471: Introduction to Artificial Intelligence | 3 Credits |
IFT 511: Analyzing Big Data / Elective 3 | 3 Credits |
EEE 554: Probability and Radom Process / Elective 4 | 3 Credits |
Deep Learning | 3 Credits |
| Total Credits | 18 Credits |
| Summer Semester 2 (Summer Session IV) | Credits |
|---|---|
Artificial Intelligence Capstone Project II | 3 Credits |
FSE 501: Technology Entrepreneurship/Entrepreneurship | 3 Credits |
CSE 463: Introduction to Human Computer Interaction / Elective 5 | 4 Credits |
CSE 4**: Elective 6 | 3 Credits |
FSE502: Strategic Enterprise Innovation / Elective 7 | 3 Credits |
| Total Credits | 16 Credits |
List Of Electives
| Electives | Credits |
|---|---|
IFT 511: Analyzing Big Data / Elective 3 | 3 Credits |
EEE 554: Probability and Radom Process / Elective 4 | 3 Credits |
FSE502: Strategic Enterprise Innovation / Elective 7 | 3 Credits |
CSE 463: Introduction to Human Computer Interaction / Elective 5 | 4 Credits |
Natural Language Processing | 3 Credits |
Speech Processing | 3 Credits |
Data Mining | 3 Credits |
Advanced Statistics | 3 Credits |
Reinforcement Learning | 3 Credits |
Fuzzy Systems | 3 Credits |
Swarm Intelligence | 3 Credits |
Agent Based Modeling | 3 Credits |
| Electives for this program should include bridge courses for MS AI in Engineering at ASU: | |
|---|---|
IFT 511: Analyzing Big Data | 3 Credits |
CSE 575: Statistical Machine Learning | 3 Credits |
FSE 501: Technology Entrepreneurship | 3 Credits |
FSE 502: Strategic Enterprise Innovation | 3 Credits |
| Total Credits | 12 Credits |