BS Artificial Intelligence
Vision
To achieve excellence in quality education and research to prepare leaders in computational and allied sciences; contributing to industrial & societal development and prosperity.
Mission
To nurture well-rounded AI professionals with creative and entrepreneurial minds by applying basic principles and concepts of intelligent computational systems for providing quality solutions having social responsibilities and moral values that can be beneficial for the industry, country, and humanity.
Program Objectives and Goals
The BS Artificial Intelligence program at HU has been designed to produce professionals who have excellent problem solving and reasoning skills to analyze, design, and create intelligent systems by thinking critically. The curriculum provides a blend of mathematical approach, statistical and classical AI and integrated computing techniques, and business-related areas to produce graduates capable of providing intelligent solutions in industry, academics, and research. After completing the program, a student will:
- Be able to impart quality education and build student’s capacity to emerge as professionals in the field of AI by acquiring deep knowledge of both computational and human sciences and learning core AI concepts and techniques.
- Be able to focus on complex multimedia inputs, such as speech, image, video, natural language, and large datasets to make decisions by applying reasoning skills.
- Be able to have appropriate communication skills and the ability to perform effectively as an individual and as a group member or entrepreneur in multi-disciplinary domains.
- Be able to provide effective technological solutions in all the diversified areas like business, healthcare, transportation, agriculture, and education, etc.
Program Summary
| Program Duration | 4 Years (7 years max.) |
| Number of Semesters | 8 |
| Average number of Courses per Semester | 5 or 6 |
| Total Credit Hours | 131 (*Additional/Deficiency courses not included while calculating CGPA for intermediate Pre-Medical Students) |
Admission Eligibility
- At least 50% marks in Intermediate (HSSC) examination with Pre-Engineering or equivalent qualification with Mathematics certified by IBCC.
- “OR” At least 50% marks in Intermediate (HSSC) examination with Pre-Medical but students must pass deficiency courses of Mathematics of 06 credit hours within one year of their regular undergraduate studies.
| Curriculum | |||
| Semester 1 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| MT-110 | Basic Mathematics-1* | 3 | – |
| GE-111 | Islamic Studies/Ethics | 2 | – |
| NS-111 | Applied Physics | 2 | – |
| NS-111L | Applied Physics Lab | 1 | – |
| UE-11X | University-Elective-1 | 3 | |
| GE-112 | English Grammar & Comprehension | 3 | – |
| GE-113 | Introduction to IT and Computing | 3 | – |
| GE-113L | Introduction to IT and Computing Lab | 1 | – |
| Semester Credit Hours | 15 | ||
| Semester 2 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| MT-120 | Basic Mathematics-2* | 3 | – |
| MT-121 | Calculus and Analytical Geometry | 3 | – |
| CS-121 | Programming Fundamentals | 3 | – |
| CS-121L | Programming Fundamentals Lab | 1 | – |
| GE-121 | Communication & Presentation Skills | 3 | – |
| CS-122 | Discrete Structures | 3 | – |
| GE-122 | Pakistan Studies | 2 | – |
| Semester Credit Hours | 15 | ||
| Semester 3 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| CS-211 | Object Oriented Programming | 3 | CS-121 |
| CS-211L | Object Oriented Programming Lab | 1 | CS-121L |
| AI-211 | Artificial Intelligence | 3 | – |
| AI-211L | Artificial Intelligence Lab | 1 | – |
| MT-211 | Probability & Statistics | 3 | – |
| MT-212 | Linear Algebra | 3 | – |
| CS-212 | Data Communications & Computer Networks | 3 | – |
| CS-212L | Data Communication & Computer Networks Lab | 1 | – |
| Semester Credit Hours | 18 | ||
| Semester 4 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| CS-221 | Data Structures & Algorithms | 3 | CS-121 |
| CS-221L | Data Structures & Algorithms Lab | 1 | CS-121L |
| CS-222 | Software Engineering | 3 | – |
| UE-22X | University-Elective-2 | 3 | |
| AI-221 | Stochastic Processes | 3 | MT-211 |
| SC-221 | Multi-variable Calculus | 3 | MT-121 |
| Semester Credit Hours | 16 | ||
| Semester 5 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| CS-311 | Database Systems | 3 | CS-221 |
| CS-311L | Database Systems Lab | 1 | CS-221L |
| CS-312 | Operating Systems | 3 | CS-221 |
| CS-312L | Operating Systems Lab | 1 | CS-221L |
| SC-311 | Numerical Computing | 2 | – |
| SC-311L | Numerical Computing Lab | 1 | – |
| AI-311 | Machine Learning | 3 | AI-221 |
| AI-311 L | Machine Learning Lab | 1 | AI-221L |
| SC-312 | Graph Theory | 3 | |
| Semester Credit Hours | 18 | ||
| Semester 6 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| CS-321 | Information Security | 3 | – |
| GE-321 | Professional Practices | 3 | – |
| AI-321 | Computer Vision and Pattern Recognition | 3 | |
| AI-321L | Computer Vision and Pattern Recognition Lab | 1 | |
| AI-322 | Design and Analysis of Algorithms | 3 | CS-221 |
| AIE-3XX | Domain Elective -1 | 3 | – |
| Semester Credit Hours | 16 | ||
| Semester 7 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| AI-411 | Final Year Project Part -I | 3 | |
| AI-412 | Natural Language Processing | 3 | |
| AI-413 | Deep Learning | 3 | |
| AIE-4XX | Domain Elective -2 | 3 / (2+1) | – |
| AIE-4XX | Domain Elective -3 | 3 / (2+1) | – |
| UE-41X | University-Elective 3 | 3 | – |
| Semester Credit Hours | 18 | ||
| Semester 8 | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| AI-421 | Final Year Project Part -II | 3 | AI-411 |
| GE-421 | Technical & Business Report Writing | 3 | – |
| UE-421 | University-Elective-4 | 3 | – |
| AIE-4XX | Domain Elective -4 | 3 / (2+1) | – |
| AIE-4XX | Domain Elective -5 | 3 / (2+1) | – |
| Semester Credit Hours | 15 | ||
| University Electives | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| UE-111 | Financial Accounting | 3 | – |
| UE-221 | Financial Management | 3 | – |
| UE-222 | Principles of Management and Economics | 3 | – |
| UE-412 | Marketing and Management | 3 | – |
| UE-411 | Human Resource Management | 3 | – |
| UE-421 | Entrepreneurship | 3 | – |
| UE-422 | Organizational Behavior | 3 | – |
| UE-112 | Foreign Languages | 3 | – |
| Artificial Intelligence (Domain) Core | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| AI-211 | Artificial Intelligence (Domain Core-1) | 3+1 | |
| AI-221 | Stochastic Processes(Domain Core-2) | 3 | MT-121 |
| AI-311 | Machine Learning(Domain Core-3) | 3+1 | |
| AI-321 | Computer Vision and Pattern Recognition(Domain Core-4) | 3 | |
| AI-322 | Design and Analysis of Algorithm | 3 | CS-221 |
| AI-411 | Natural Language Processing(Domain Core-5) | 3 | AI-311 |
| AI-412 | Deep Learning(Domain Core-6) | 3 | |
| AI Elective | |||
| Course Code | Course Title | Cr. Hrs | Pre-requisite |
| AIE-4XX | Expert Systems | 3 | |
| AIE-4XX | Graph Theory | 3 | |
| AIE-4XX | Special Topics in AI | 3 | |
| AIE-3XX | Human Computer Interaction | 3 | |
| AIE-4XX | Data Warehousing and Data Mining | 3/(2+1) | |
| AIE-3XX | Introduction to Bioinformatics | 3 | |
| AIE-4XX | Design of IoT | 3 | |
| AIE-3XX | High Performance Computing | 3 | |
| AIE-4XX | Medical Imaging | 3 | |
| AIE-3XX | Introduction to Robotics | 3 | |
| AIE-4XX | Special Topics in AI | 3 | |
| AIE-3XX | Computational Cognitive Sciences | 3 | |
| AIE-4XX | Motion Planning | 3 | |
| AIE-4XX | Cybernetics | 3 | |
| AIE-3XX | Information Retreival | 3 | |
| AIE-4XX | Optimization Techniques | 3 | |
| AIE-4XX | Virtual & Augmented Reality | 3 | |
| For Pre-Medical | |||
| Basic Mathematics 1 Course Contents | Basic Mathematics 2 Course Contents | ||
| Number Systems (Rationale, Irrationale, Complex) | Induction theory (Mathematical Induction & Binomial Theorem) | ||
| Set Theory (Operations, Properties, Venn | Differentiation | ||
| Fractions (Rationale, Proper, Improper) | Integration | ||
| Quadratic Equation | Permutation and Combination | ||
| Sequence Series (Arithmatic, Geomatric, Harmonic) | |||
For Admission Inquiries
Cell No: +92-302-1025864
Email: muhammad.faheem@hamdard.edu.pk, saher.shimail@hamdard.edu.pk
General Information
Contact Info
Hamdard University, Madinat al-Hikmah
Hakim Mohammed Said Road
Karachi – 74600, Pakistan
P : (92-21) 36440035-40
Admission : (92-21) 36440041-42
(92-21) 34531130 (92-21) 4559779
F : (92-21) 36440045
Email: info@hamdard.edu.pk
Hakim Mohammed Said Road
Karachi – 74600, Pakistan
P : (92-21) 36440035-40
Admission : (92-21) 36440041-42
(92-21) 34531130 (92-21) 4559779
F : (92-21) 36440045
Email: info@hamdard.edu.pk
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