BS in Artificial Intelligence


PROGRAM EDUCATIONAL OBJECTIVES (PEO)

  1. Knowledge of the fundamentals of Computing and Artificial Intelligence: Our graduates will be proficient in the fundamentals of computing and artificial intelligence knowledge and will be read to apply that in professional roles in industry, academia, or a startup.
  2. Ethical and Societal Responsibilities: Our graduates will be able to work professionally with dignity and integrity by taking into account the ethical and social concerns.
  3. Communication Skills: Our graduates will possess effective oral and verbal communication ability in technical and managerial roles.
  4. Leadership: Our graduates will excel in a leadership capacity within a team or in a business setting.
  5. Continuous Improvement: Our graduates will be able to explore newly emerging fields in computing and artificial intelligence for her job role or academic purposes.

PROGRAM LEARNING OUTCOMES (PLOs)
This program prepares students to attain educational objectives by ensuring that students demonstrate achievement of the following outcomes:

  1. Academic Education To prepare graduates as computing professionals.
  2. Knowledge for Solving Computing Problems Apply knowledge of computing fundamentals, knowledge of a computing specialization, and mathematics, science, and domain knowledge appropriate for the computing specialization to the 16 abstraction and conceptualization of computing models from defined problems and requirements
  3. Problem Analysis Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines
  4. Design/ Development of Solutions Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations
  5. Modern Tool Usage Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations
  6. Individual and Team Work Function effectively as an individual and as a member or leader in diverse teams and in multi-disciplinary settings.
  7. Communication Communicate effectively with the computing community and with society at large about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.
  8. Computing Professionalism and Society Understand and assess societal, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice.
  9. Ethics Understand and commit to professional ethics, responsibilities, and norms of professional computing practice.
  10. Life-long Learning Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.

CURRICULUM FOR BS (ARTIFICIAL INTELLIGENCE) PROGRAM


Semester

Course(s) Code (New)

Course(s) Title

Credit Hours

Prerequisite

Semester I

AIN101

Applied Physics

3 + 1

 

AIN111

Introduction to Information and Communication Technology

3 + 1

 

AIN102

Calculus and Analytical Geometry

3 + 0

 

HUM111

Functional English

3 + 0

 

HS102

Islamic Studies

2 + 0

 

HS103

Pakistan Studies

2 + 0

 

 

Total Semester Credit Hours

(16 + 2)

 

Semester II

HUM233

Philosophy and Critical Thinking

3 + 0

 

HUM231

Communication Skills

3 + 0

HUM111

 

AIN131

Programming Fundamentals

3 + 1

AIN111

 

AIN103

Linear Algebra and Differential Equations

3 + 0

AIN102

 

HUM112

Personal Development

3 + 0

 

 

Total Semester Credit Hours

(15 + 1)

 

Semester III

AIN221

Operating Systems

3 + 1

AIN101, AIN131

 

AIN231

Object Oriented Programming

3 + 1

AIN131

 

AIN201

Probability and Statistics

3 + 0

AIN102

 

SSC231

World History

   3 + 0

HUM111

 

AIN202

Multivariate Calculus

3 + 0

AIN102

 

 

Total Semester Credit Hours

(15 + 2)

 

Semester IV

AIN232

Data Structures & Algorithms

3 + 1

AIN231

 

AIN233

Database Management Systems

3 + 1

AIN221
AIN231

 

AIN241

Discrete Structures

3 + 0

AIN202

 

AIN203

Applied Statistics

3 + 0

AIN201

 

AIN261

Data Communication and Computer Networks

3 + 1

AIN221

 

HUM113

Sociology

3 + 0

 

 

Total Semester Credit Hours

(18 + 3)

 

Semester V

AIN371

Artificial Intelligence

3 + 1

AIN232

 

AIN342

Design and Analysis of Algorithms

3 + 0

AIN232

 

AIN372

Continuous and Discrete Optimization

3 + 1

AIN103, AIN202, AIN203

 

    HUM241

World Literature

   3 + 0

HUM111

 

AIN351

Software Engineering

3 + 0

AIN231

 

 

Total Semester Credit Hours

(15 + 2)

 

Semester VI

AIN373

Machine Learning

3 + 1

AIN371, AIN372

 

AIN374

Logic & Automated Reasoning

3 + 0

AIN371

 

HUM121

Academic Writing

3 + 0

HUM111

 

AIN375

Data Visualization

3 + 1

AIN202
AIN203

 

AIN331

Parallel and Distributed Computing

3 + 1

AIN231
AIN261

 

 

Total Semester Credit Hours

(15 + 3)

 

Semester VII

AIN471

Final Year Project – I

0 + 3

AIN351
AIN373

 

AIN472

Natural Language Processing

3 + 1

AIN373

 

AINXXX

Elective I

3 + 0

 

AIN473

Computer Vision

3 + 1

AIN373

 

AINXXX

Elective II

3 + 0

 

 

Total Semester Credit Hours

(12+ 5)

 

Semester VIII

AINXXX

Elective III

3 +  0

 

AIN474

Deep Learning

3 +  1

AIN373

 

AIN475

Final Year Project – II

0 + 3

AIN471

 

AIN476

Artificial Intelligence for Robotics

3 +  0

AIN472, AIN374

 

HUM232

Ethics & Social Responsibility

3 + 0

 

 

Total Semester Credit Hours

(12 + 4)

 

Program Total Credit Hour(s): 140



List of Elective Courses for BS (Artificial Intelligence)

 

Course Code

Course(s) Title

Credit Hours

AINX7X

Natural Language Processing

3 + 0

AINX7X

Artificial Intelligence for Robotic Systems

3 + 0

AINX7X

Security Analytics

3 + 0

AINX7X

Reinforcement Learning

3 + 0

AINX7X

Image Processing & Analysis

3 + 0

AINX7X

Probabilistic Graphical Models

3 + 0

AINX7X

High-Performance Computing

3 + 0

AINX7X

Big Data Analytics

3 + 0

AINX7X

Social Media Mining

3 + 0

AINX7X

Metaheuristic Optimization

3 + 0

AINX7X

Security & Privacy

3 + 0