Introduction
The Department of Computer Science, in keeping with the needs of the modern education requirement in technology, is introducing a Bachelors in Data Science program. The BS (Data Science) has a dual emphasis on basic principles of statistics and computer science, with foundational training in statistical and mathematical aspects of data analysis. This program develops a foundation on broad computer science principles, including algorithms, data structures, data management and machine learning. This program will prepare graduates for a career in data analysis, combining foundational statistical concepts with computational principles from computer science.
OBJECTIVES
- Develop proficiency in programming languages used in data science.
- Develop strong mathematical and statistical skills to analyze data and draw insights from data.
- Learn to use data visualization tools and techniques to communicate insights effectively.
- Acquire knowledge of big data technologies and platforms for managing and processing large datasets.
- Develop an understanding of data ethics and privacy issues in data science.
- Learn to work with unstructured data such as text, images, and videos.
PROGRAM FEATURES
- The updated BS (DS) is a 133 credit hours program and may be completed in minimum four years (eight semesters).
- Two semesters are offered in a year, Spring and Autumn.
- Duration of each semester is 18 weeks.
- 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(DS). 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
Merit Base
Duration
Medium of Instruction
Teaching Methodology
The program is offered in Face-to-Face Mode in both main campus and regions.
Total Credits Hours Required
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
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 |
Engl 3505 |
Functional English |
GER |
3 (3+0) |
|
6 |
MATh3517 |
Pre-Calculus 1 |
None |
N/C |
|
|
|
|
Total |
16(14+2) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
6902 |
Object Oriented Programming |
Core |
4 (3+1) |
|
2 |
6907 |
Database Systems |
Core |
4 (3+1) |
|
3 |
6937 |
Digital Logic Design |
Core |
3 (2+1) |
|
4 |
4433 |
Calculus-II |
Maths |
3 (3+0) |
|
5 |
1522 |
Linear Algebra |
Maths |
3 (3+0) |
|
6 |
New |
Pre-Calculus 2 |
None |
N/C |
|
|
|
|
Total |
17 (14+3) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
6904 |
Data Structures |
Core |
4 (3+1) |
|
2 |
6938 |
Information Security |
Core |
3 (2+1) |
|
3 |
6939 |
Artificial Intelligence |
Core |
3 (2+1) |
|
4 |
6940 |
Computer Networks |
Core |
3 (2+1) |
|
5 |
6906 |
Software Engineering |
Core |
3 (3+0) |
|
6 |
3447 |
Probability & Statistics |
Maths |
3 (3+0) |
|
|
|
|
Total |
19 (15+4) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
6941 |
Computer Organization & Assembly Language |
Core |
3 (2+1) |
|
2 |
New |
Introduction to Data Science |
Domain Core |
3 (2+1) |
|
3 |
New |
Advanced Statistics |
Domain Core |
3 (2+1) |
|
4 |
6923 |
Applied Physics |
GER |
3 (2+1) |
|
5 |
ENGL3504 |
Expository Writing |
GER |
3(3+0) |
|
6 |
ITHC3501/ HADH3501 |
GER |
2 (2+0) |
|
|
|
|
|
Total |
17 (13+4) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
6945 |
Operating Systems |
Core |
3 (2+1) |
|
2 |
New |
Data Mining |
Domain Core |
3 (2+1) |
|
3 |
New |
Data Visualization |
Domain Core |
3 (2+1) |
|
4 |
3466 |
Analysis and Design of Algorithms |
Core |
3 (3+0) |
|
5 |
New |
Domain Elective (Big Data Analytics) |
Dom Elective 1 |
3 (2+1) |
|
6 |
MGT3504 |
Introduction to Management |
GER |
2 (2+0) |
|
7 |
SERT3501 |
Fahm-E-Quran (Tajwid, Translation and Tafsir) |
Non-Credit |
(NC) |
|
|
|
|
Total |
17 (12+5) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
New |
Data Warehousing & Business Intelligence |
Domain Core |
3 (2+1) |
|
2 |
6911/6980 |
Parallel & Distributed Computing |
Domain Core |
3 (2+1) |
|
3 |
New |
Domain Elective(Machine Learning) |
Dom Elective 2 |
3 (2+1) |
|
4 |
New |
Artificial Neural Networks & Deep Learning |
Dom Elective 3 |
3 (2+1) |
|
5 |
New |
Theory of Automata |
Dom Elective 4 |
3 (2+1) |
|
6 |
3449 |
Human Computer Interaction |
Dom Elective 5 |
3 (2+1) |
|
7 |
TFSR 3501 |
Seerat-e-Tayyaba |
Non-Credit |
(NC) |
|
|
|
|
Total |
18 (12+6) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
6981 |
Final Year Project - I |
Core |
2 (0+2) |
|
2 |
New |
Advance Database Management Systems |
Dom Elective 6 |
3 (2+1) |
|
3 |
New |
Topics in Data Science |
Dom Elective 7 |
3 (2+1) |
|
4 |
3442 |
IT Marketing Concepts |
SS |
3 (3+0) |
|
5 |
5454 |
Technical & Business Writing |
GER |
3 (3+0) |
|
6 |
MGT3503 |
Entrepreneurship |
GER |
2 (2+0) |
|
7 |
New |
Internship |
- |
3 (0+3) |
|
|
|
|
Total |
19(16+3) |
|
S# |
Code |
Course Title |
Domain |
Cr hr |
|
1 |
6982 |
Final Year Project -II |
Core |
4 (0+4) |
|
2 |
PKST3502 |
Ideology and Constitution of Pakistan |
GER |
2 (2+0) |
|
3 |
6984 |
Professional Practices |
GER |
2 (2+0) |
|
4 |
SOC3503 |
Civics and Community Engagement |
GER |
2 (2+0) |
|
|
|
|
Total |
10 (6+4) |
1
2
3
4
5
6
Semesters
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).