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) ODL 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.
Program 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.
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
Admission will be given to all candidates satisfying the eligibility and merit criteria, subject to a viable group of students.
Duration
Medium of Instruction
Teaching Methodology
Open Distance Learning
Total Credits Hours Required
|
S# |
Code |
Course Title |
Domain |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS3002 |
Computer Programming |
Core |
4 (3+1) |
|
2 |
CS3003 |
Applications of Information & Communication Technologies |
GER |
3 (2+1) |
|
3 |
MATH3005 |
Discrete Mathematics |
GER-QR1 |
3 (3+0) |
|
4 |
MATH3004 |
Calculus-I |
GER-QR2 |
3 (3+0) |
|
5 |
ENGL3001 |
Functional English |
GER |
3 (3+0) |
|
Total |
16 (14+2) |
|
S# |
Code |
Course Title |
Domain |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS3004 |
Object Oriented Programming |
Core |
4 (3+1) |
|
2 |
CS3005 |
Database Systems |
Core |
4 (3+1) |
|
3 |
CS3006 |
Digital Logic Design |
Core |
3 (2+1) |
|
4 |
MATH3006 |
Calculus-II |
Maths |
3 (3+0) |
|
5 |
MATH3007 |
Linear Algebra |
Maths |
3 (3+0) |
|
Total |
17 (14+3) |
|
S# |
Code |
Course Title |
Domain |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS4001 |
Data Structures and Algorithms |
Core |
4 (3+1) |
|
2 |
CS4002 |
Information Security |
Core |
3 (2+1) |
|
3 |
CS4003 |
Artificial Intelligence |
Core |
3 (2+1) |
|
4 |
CS4004 |
Computer Networks |
Core |
3 (2+1) |
|
5 |
CS4005 |
Software Engineering |
Core |
3 (3+0) |
|
6 |
STAT4001 |
Statistics & Probability |
Maths |
3 (3+0) |
|
Total |
19 (15+4) |
|
S# |
Code |
Course Title |
Domain / Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS4006 |
Computer Organization & Assembly Language |
Core |
3 (2+1) |
|
2 |
CS4007 |
Introduction to Data Science |
Domain Core |
3 (2+1) |
|
3 |
CS4008 |
Advanced Statistics |
Domain Core |
3 (2+1) |
|
4 |
PHY4001 |
Applied Physics |
GER |
3 (2+1) |
|
5 |
ENGL3002 |
Expository Writing |
GER |
3 (3+0) |
|
6 |
ITHC3009 / HADH3008 |
Islamic Studies / Ethics |
GER |
3 (3+0) |
|
7 |
PKST3002 |
Pakistan Studies |
|
3 (3+0) |
|
S# |
Code |
Course Title |
Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS5001 |
Operating Systems |
Core |
3 (2+1) |
|
2 |
CS5002 |
Data Mining |
Domain Core |
3 (2+1) |
|
3 |
CS5003 |
Data Visualization |
Domain Core |
3 (2+1) |
|
4 |
CS5004 |
Analysis and Design of Algorithms |
Core |
3 (3+0) |
|
5 |
CS5005 |
Big Data Analytics |
Domain Elective¹ |
3 (2+1) |
|
6 |
MGT3001 |
Introduction to Management |
GER |
3 (3+0) |
|
7 |
TFSR3001 |
Fahm-e-Quran (Tajwid, Translation & Tafsir) |
Non-Credit (N/C) |
|
|
S# |
Code |
Course Title |
Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS5006 |
Data Warehousing & Business Intelligence |
Domain Core |
3 (2+1) |
|
2 |
CS5007 |
Parallel & Distributed Computing |
Domain Core |
3 (2+1) |
|
3 |
CS5008 |
Machine Learning |
Domain Elective 2 |
3 (2+1) |
|
4 |
CS5009 |
Artificial Neural Networks & Deep Learning |
Domain Elective 3 |
3 (2+1) |
|
5 |
CS5010 |
Theory of Automata |
Domain Elective 4 |
3 (2+1) |
|
6 |
CS5011 |
Human-Computer Interaction (HCI) |
Domain Elective 5 |
3 (2+1) |
|
7 |
SERT3001 |
Seerat-e-Tayyaba |
Non-Credit (N/C) |
— |
|
Total |
18 (12+6) |
|
S# |
Code |
Course Title |
Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS6001 |
Final Year Project – I |
Core |
2 (0+2) |
|
2 |
CS6002 |
Advanced Database Management Systems |
Domain Elective 6 |
3 (2+1) |
|
3 |
CS6003 |
Topics in Data Science |
Domain Elective 7 |
3 (2+1) |
|
4 |
CS6004 |
IT Marketing Concepts |
Social Sciences (SS) |
3 (3+0) |
|
5 |
ENGL3003 |
Technical & Business Writing |
GER |
3 (3+0) |
|
6 |
MGT3002 |
Entrepreneurship |
GER |
3 (3+0) |
|
7 |
CS6005 |
Internship |
— |
3 (0+3) |
|
Total |
20 (13+7) |
|
S# |
Code |
Course Title |
Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
CS6006 |
Final Year Project – II |
Core |
4 (0+4) |
|
2 |
PKST3001 |
Ideology and Constitution of Pakistan |
GER |
3 (3+0) |
|
3 |
CS6007 |
Professional Practices |
GER |
3 (3+0) |
|
4 |
SOC3001 |
Civics and Community Engagement |
GER |
3 (3+0) |
|
Total |
13 (9+4) |
Elective / Major Courses:
Data Science Core– Course Contents
|
S# |
Course Code (Tentative) |
Course Title |
Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
DS5001 (e.g.) |
Advanced Statistics |
Data Science Core |
3 (3+0) |
|
2 |
DS5002 |
Big Data Analytics |
Data Science Core |
3 (2+1) |
|
3 |
DS5003 |
Data Mining |
Data Science Core |
3 (2+1) |
|
4 |
DS5004 |
Data Visualization |
Data Science Core |
3 (2+1) |
|
5 |
DS5005 |
Data Warehousing and Business Intelligence |
Data Science Core |
3 (2+1) |
|
6 |
DS5006 |
Introduction to Data Science |
Data Science Core |
3 (2+1) |
Data Science Elective– Course Contents
|
S# |
Course Code |
Course Title |
Category |
Credit Hours |
|---|---|---|---|---|
|
1 |
New |
Advanced Database Management Systems |
Data Science Elective |
3 (2+1) |
|
2 |
New |
Big Data Analytics |
Data Science Elective |
3 (2+1) |
|
3 |
New |
Machine Learning |
Data Science Elective |
3 (2+1) |
|
4 |
New |
Artificial Neural Networks & Deep Learning |
Data Science Elective |
3 (2+1) |
|
5 |
New |
Theory of Automata |
Data Science Elective |
3 (3+0) |
|
6 |
New |
HCI & Computer Graphics |
Data Science Elective |
3 (2+1) |
|
7 |
New |
Topics in Data Science |
Data Science Elective |
3 (2+1) |
2
3
4
5
Semesters
Workshop
The online workshop for each course will comprise of 12 hours, with 2 hours daily for 6 days except for the teaching practice and project as per AIOU policy. Each semester will have a workshop for the courses offered in that particular semester. There will be an online quiz for every course at the end of the workshop.
Assessment Weightage
| Assignments (Weightage) | Workshop (Attendance & Quizzes) (Weightage) | Final Exam (Weightage) | Passing Marks |
| 20% | 30% Quiz | 50% | 50% (in aggregate). However, 40% marks in final exams is mandatory. |
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).