BS (Artificial Intelligence) With Deficiency Course

Introduction

In this era of machine intelligence and robotics, artificial intelligence is the need of the time. The Department of Computer Science, in keeping with the needs of the modern education requirement in technology, is introducing a Bachelors in Artificial Intelligence program. The BS (Artificial Intelligence) gives the students an in-depth knowledge they need to transform large and complex scenarios into actionable decisions. The program and its curriculum focus on how complex inputs such as knowledge, vision, language and huge databases can be used to make decisions to enhance human capabilities. The curriculum of the BS (AI) program includes coursework in computing, mathematics, automated reasoning, statistics, computational modeling, introduction to classical artificial intelligence languages and case studies, knowledge representation and reasoning, artificial neural networks, machine learning, natural language processing, vision and symbolic computation. The program also encourages students to take courses in ethics and social responsibility, with the opportunity to participate in long term projects in which artificial intelligence.

MISSION

To provide accessible, high-quality Artificial Intelligence education that builds strong mathematical, computational and intelligent-systems skills. The program prepares ethical, innovative graduates who can turn complex data and knowledge into sound decisions, for careers, higher education and leadership in the digital future.

OBJECTIVES

  • Develop proficiency in programming languages used in Artificial Intelligence.
  • Develop strong mathematical skills to understand and to analyze the different paradigms of Artificial Intelligence.
  • Learn to manipulate complex input such as knowledge, vision, language etc. to make decisions.
  • Develop an understanding of data ethics and privacy issues in Artificial Intelligence.
  • Learn to develop new frameworks for solving different problems.

OUTCOMES (HEC/NCEAC Computing PLOs)

PLO

Title

Outcome for BS-AI

PLO-1

Academic Education

Complete the program in a way that prepares graduates as AI professionals.

PLO-2

Knowledge for Solving Computing Problems

Apply mathematics, statistics, algorithms and AI fundamentals, including machine learning and knowledge representation, to solve computing problems.

PLO-3

Problem Analysis

Identify, analyze and formulate complex problems that call for intelligent solutions.

PLO-4

Design/Development of Solutions

Design and develop AI-based solutions, such as machine learning, natural language processing and vision systems, that meet specified needs.

PLO-5

Modern Tool Usage

Select and apply modern AI languages, frameworks and tools.

PLO-6

Individual and Teamwork

Work effectively as an individual and as a member or leader of teams.

PLO-7

Communication

Communicate technical findings effectively through documentation, reports and presentations.

PLO-8

Computing Professionalism and Society

Understand the legal, social and cultural impact of AI systems.

PLO-9

Ethics

Apply professional ethics, data ethics and privacy principles in AI practice.

PLO-10

Life-long Learning

Engage in independent learning to keep pace with rapidly evolving AI technologies.

PROGRAM FEATURES

  1. The updated BS(AI) is a 135 credit hours program and may be completed in minimum four years (eight semesters).
  2. Two semesters are offered in a year, Spring and Autumn.
  3. Duration of each semester is 18 weeks.
  4. Program is In-line with HEC.

Eligibility Criteria

Minimum 50% marks in Intermediate/12 years schooling/A-Level (HSSC) or Equivalent with Mathematics are required for admission in BS(AI). Equivalency certificate by IBCC will be required in case of education from some other country or system. The students who have not studied Mathematics at intermediate level have to pass deficiency courses of Mathematics ((non-credit)) in first two semesters

Selection Process

Open Merit

Duration

4 Years

Medium of Instruction

English

Teaching Methodology

The program is offered in Face-to-Face Mode

Total Credits Hours Required

135

S#

Code

Course Title

Domain

Credit Hours

1

CS3504

Computer Programming

Core

4 (3+1)

2

CS3503

Applications of Information & Communication Technologies

GER

3 (2+1)

3

MATH3516

Discrete Mathematics

GER-QR1

3 (3+0)

4

MATH3502

Calculus-I

GER-QR2

3 (3+0)

5

ENGL3505

Functional English

GER

3 (3+0)

6

MAH3517

Pre-Calculus-I

Deficiency Course

N/C
   

Total Credit Hours

  

16 (14+2)

S#

Code

Course Title

Domain

Credit Hours

1

CS3506

Object Oriented Programming

Core

4 (3+1)

2

CS3507

Database Systems

Core

4 (3+1)

3

CS3508

Digital Logic Design

Core

3 (2+1)

4

MATH3509

Calculus-II

Maths

3 (3+0)

5

MATH3512

Linear Algebra

Maths

3 (3+0)

6

MATH3518

Pre-Calculus-II

Deficiency Course

N/C
   

Total Credit Hours

  

17 (14+3)

S#

Code

Course Title

Domain

Credit Hours

1

CS4521

Data Structures and Algorithms

Core

4 (3+1)

2

CS4522

Information Security

Core

3 (2+1)

3

CS4523

Artificial Intelligence

Core

3 (2+1)

4

CS4524

Computer Networks

Core

3 (2+1)

5

CS4525

Software Engineering

Core

3 (3+0)

6

STAT4509

Statistics & Probability

Maths

3 (3+0)
   

Total Credit Hours

  

19 (15+4)

S#

Code

Course Title

Domain

Credit Hours

1

CS4526

Computer Organization & Assembly Language

Core

3 (2+1)

2

CS4531

Programming for AI

Domain Core

3 (2+1)

3

CS5501

Machine Learning

Domain Core

3 (2+1)

4

PHY4509

Applied Physics

GER

3 (2+1)

5

ENGL3504

Expository Writing

GER

3 (3+0)

6

ITHC3501 / HADH3501

Islamic Studies / Ethics

GER

2 (2+0)

7

PKST3501

Pakistan Studies

GER

2 (2+0)
   

Total Credit Hours

  

19 (15+4)

S#

Code

Course Title

Domain / Category

Credit Hours

1

CS5502

Operating Systems

Core

3 (2+1)

2

CS6514

Artificial Neural Networks & Deep Learning

Domain Core

3 (2+1)

3

CS5522

Knowledge Representation and Reasoning

Domain Core

3 (2+1)

4

CS6502

Analysis and Design of Algorithms

Core

3 (3+0)

5

—

Domain Elective I

Domain Elective

3 (2+1)

6

MGT3504

Introduction to Management

GER

2 (2+0)

7

TFSR3501

Fahm-e-Quran (Tajwid, Translation & Tafsir)

Non-Credit

(NC)
   

Total Credit Hours

  

17 (14+3)

S#

Code

Course Title

Domain / Category

Credit Hours

1

CS6516

Computer Vision

Domain Core

3 (2+1)

2

CS5506

Parallel & Distributed Computing

Domain Core

3 (2+1)

3

—

Domain Elective II

Domain Elective

3 (2+1)

4

—

Domain Elective III

Domain Elective

3 (2+1)

5

—

Domain Elective IV

Domain Elective

3 (2+1)

6

—

Domain Elective V

Domain Elective

3 (2+1)

7

SERT3501

Seerat-e-Tayyaba

Non-Credit

(NC)
   

Total Credit Hours

  

18 (12+6)

S#

Code

Course Title

Domain / Category

Credit Hours

1

CS6501

Final Year Project – I

Core

2 (0+2)

2

—

Domain Elective VI

Domain Elective

3 (2+1)

3

—

Domain Elective VII

Domain Elective

3 (2+1)

4

CS6503

IT Marketing Concepts

Social Sciences (SS)

3 (3+0)

5

ENGL3503

Technical & Business Writing

Maths & Support

3 (3+0)

6

MGT3503

Entrepreneurship

GER

2 (2+0)

7

CS6507

Internship

—

3 (0+3)
   

Total Credit Hours

  

19 (12+7)

S#

Code

Course Title

Domain

Credit Hours

1

CS6504

Final Year Project – II

Core

4 (0+4)

2

PKST3502

Ideology and Constitution of Pakistan

GER

2 (2+0)

3

CS6506

Professional Practices

GER

2 (2+0)

4

SOC3503

Civics and Community Engagement

GER

2 (2+0)
   

Total Credit Hours

  

10 (6+4)

Elective / Major Courses:

Domain Elective 01

S#

Code

Course Title (HEC 2023)

Credit Hours

2

STAT6511

Data Mining

3 (2+1)
   

Total

3 (2+1)

Domain Electives 02 – 05

S#

Code

Course Title (HEC 2023)

Credit Hours

5

CS6517

Swarm Intelligence

3 (2+1)

6

CS6518

Fuzzy Systems

3 (2+1)

7

CS6519

Reinforcement Learning

3 (2+1)

8

CS6520

Advanced Statistics

3 (2+1)
   

Total

12 (8+4)

Domain Electives 06 – 07

S#

Code

Course Title (HEC 2023)

Credit Hours

3

CS6521

Natural Language Processing

3 (2+1)

4

CS4527

Theory of Automata

3 (2+1)
   

Total

6 (4+2)

2

3

4

5

6

Semesters

08

Assessment Weightage

For Theory Courses:
S.No. Components Total Marks Weightage Passing Marks
1 Assignment 10 20% 50% (In aggregate)
2 Assignment 2 10
3 Mid Term 30 30%
4 Attendance 100 Nil 70%
5 Final Exam 100 50% 50%
For Theory-Practical Courses:
S.No. Components Total Marks Weightage Passing Marks
1 Assignment 10 20% 50% (In aggregate)
2 Assignment 2 10
3 Mid Term 30 30%
4 Practical 15
5 Attendance 100 Nil 70%
6 Final Exam 100 50% 50%
For Practical/FYP Courses:
S.No. Components Total Marks Weightage Passing Marks
1 Attendance 100 Nil 70%
2 Final Exam 100 100% 50%

Note: Allama Iqbal Open University (AIOU) reserves the right to amend the fee structure policy, course offering and assessment of courses when required. The existing course(s) will be adopted/adapted as per requirement. The department may change the sequence of the course(s) offering as per availability of course(s).

About

The Allama Iqbal Open University was established in May, 1974, with the main objectives of providing educational opportunities to masses and to those who cannot leave their homes and jobs. During all these past years, the University has more than fulfilled this promise.