Associate Degree Program in Computer Science
The Computer Science Department of the virtual university offers a 2-year associate degree Program in computer science which is equivalent to a 14-year bachelor’s degree. The program’s primary objective is to provide students with technical skills and hands-on experience in computer science fundamentals.
This program covers basic skills required to develop software systems, databases, websites, and computer networks, equipping students for entry-level career opportunities in the computer science sector and higher studies.
Candidates who hold an associate degree can either continue towards their respective four-year BS Data Science degree program, or they can apply for new admission to any four-year BS degree program (subject to meeting admission eligibility criteria and exemption/transfer policy).
Objectives
- Gain in-depth knowledge of core data science concepts, including machine learning methods (supervised, unsupervised, and semi-supervised learning), data mining, and both prescriptive and predictive analytics to handle complex data challenges across the data lifecycle.
- Leverage advanced analytical tools such as statistics, time series forecasting, optimization, and simulation to create and implement robust models for accurate data analysis and prediction.
- Discover how to identify, collect, and combine diverse data sources—including social media, public datasets, and government data—using contemporary data engineering techniques.
- Employ a range of performance and accuracy metrics to validate models, test hypotheses, and retrieve information effectively within data science initiatives.
- Integrate data analytics into business operations and workflows to support responsive decision-making and improve organizational performance.
- Master the art of visual communication by presenting analytical outcomes through dynamic dashboards and compelling data storytelling strategies.
- Exhibit strong analytical thinking and uphold ethical, professional, and social standards while making responsible decisions in data science practice.
- Develop effective communication strategies to engage both technical and non-technical audiences, fostering leadership, teamwork, and career advancement in the data science field.
Eligibility
- To be admitted to the associate degree Program, applicants must have obtained a minimum of 50% marks in their Intermediate (Part I and II)
- Deficiency courses: Students who did not pass Mathematics at the required (Intermediate) level mentioned above point can apply, but they need to complete two additional 6-credit hour Mathematics courses in the first two semesters.
- “Zero Semester” is not applicable
- The General Certificate of Secondary Education (GCSE) ‘O’ levels and School Certificate (SC) exams are equivalent to Matriculation, and grades in 6 subjects are considered.
- Additionally, the GCE ‘A’ level candidates are required to have passed 3 subjects and must provide an equivalence certificate from Inter Board Committee of Chairman (IBCC), Islamabad.
This program allows course exemption.
Degree Duration
This program is a two-year full-time course, divided into four semesters, each semester has at least 18 weeks for teaching and examinations.
Study Scheme
Semester 1
| Course Code | Subject Title | Type | Pre Requisite | Credit Hours | Specialization |
|---|---|---|---|---|---|
|
CS101
|
Introduction to Computing |
Required |
|
3 (Theory:3), Practical:0) |
|
|
MGT602
|
Entrepreneurship |
Required |
|
3 (Theory:3), Practical:0) |
|
|
ENG101 |
English Comprehension |
Required |
|
3 (Theory:3), Practical:0) |
|
|
MTH202 |
Discrete Mathematics |
Required |
|
3 (Theory:3), Practical:0) |
|
|
MTH501 |
Linear Algebra |
Required |
|
3 (Theory:3, Practical:0) |
|
|
MTH100 |
General Mathematics |
Deficiency |
|
3 (Theory:0, Practical:1) |
|
|
VU001 |
Introduction to e-Learning |
Required |
|
1 (Theory:1), Practical:0) |
|
|
ETH202 |
Ethics (for Non-Muslims) |
Elective |
|
2 (Theory:2, Practical:0) |
|
|
ISL202 |
Islamic Studies |
Elective |
|
2 (Theory:2, Practical:0) |
|
Semester 2
| Course Code | Subject Title | Type | Pre Requisite | Credit Hours | Specialization |
|---|---|---|---|---|---|
|
CS205
|
Information Security |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS306
|
Introduction to Python |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS442 |
Introduction to Data Science |
Required |
|
3 (Theory:3), Practical:0) |
|
|
ENG201 |
Business and Technical English Writing |
Required |
|
3 (Theory:3), Practical:0) |
|
|
STA301 |
Statistics and Probability |
Required |
|
3 (Theory:3), Practical:0) |
|
|
MTH104 |
Sets and Logic |
Deficiency |
|
1 (Theory:0, Practical:1) |
|
|
PAK301 |
Pakistan Studies |
Required |
|
2 (Theory:2, Practical:0) |
|
|
CS306P |
Introduction to Python (Practical) |
Required |
|
1 (Theory:0, Practical:1) |
|
Semester 3
| Course Code | Subject Title | Type | Pre Requisite | Credit Hours | Specialization |
|---|---|---|---|---|---|
|
CS403
|
Database Management Systems |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS628
|
Machine Learning |
Required |
|
3 (Theory:3), Practical:0) |
|
|
STA302 |
Data Analytics and Business Intelligence |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS435 |
Cloud Computing |
Elective |
|
3 (Theory:3), Practical:0) |
|
|
CS441 |
Big Data Concepts |
Elective |
|
3 (Theory:3), Practical:0) |
|
|
CS514 |
Internet of Things (IoT) |
Elective |
|
3 (Theory:3, Practical:0) |
|
|
CS641 |
Big Data Analytics |
Elective |
|
3 (Theory:3, Practical:0) |
|
|
STA621 |
Time Series Analysis |
Elective |
|
3 (Theory:3, Practical:0) |
|
Semester 4
| Course Code | Subject Title | Type | Pre Requisite | Credit Hours | Specialization |
|---|---|---|---|---|---|
|
CS519
|
Final Project |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS620
|
Modelling and Simulation |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS626 |
Data Mining Techniques |
Required |
|
3 (Theory:3), Practical:0) |
|
|
CS513 |
Advanced Data Analytics and Business Intelligence |
Elective |
|
3 (Theory:3), Practical:0) |
|
|
CS614 |
Data Warehousing |
Elective |
|
3 (Theory:3), Practical:0) |
|
|
MGT101 |
Financial Accounting |
Elective |
|
3 (Theory:3, Practical:0) |
|
|
CS631 |
Deep Learning |
Elective |
|
3 (Theory:3, Practical:0) |
|
Assessment of Study Progress
Semester Work | Apply | Graded/non-graded | Marks | Count |
Quizzes | a | Graded | 10-20% | 2-4 /course |
GDBs/Viva | a | 1/course | ||
Assignments/Project | a | 2-4 / Course | ||
MDBs | a | Non-Graded |
| 1 / Lecture (Module) |
Lab Work | a | Non-Graded |
| 1/Week |
Teaching Practice | c |
|
|
|
Live Sessions | a | Non-Graded |
| 1 / Week |
Attendance | c |
|
|
|
Mid Term Exam | a | Graded | 20-30% | 1 /Course |
Final Term Exam | a | Graded | 60% | 1/Course |
Any Other (Please specify) | c |
|
|
|
Total | 100% |
| ||
Project
In the final semester of the program, students must complete a 3-credit hour project of their choosing. While students have the freedom to choose their project, it is mandatory to obtain approval from their student advisor
Degree Awarded
To qualify for the associate degree program in computer science, a student is required to complete at least 72 credit hours and attain a minimum Cumulative Grade Point Average (CGPA) of 2.00 out of 4.
Fee Structure
| Degree Program | Admission Fee | Registration Fee | Security Fee | Admission Processing Fee | Semester Enrollment Fee | Per credit hour fee | Fee of Convocation | Fee payable at admission |
|---|---|---|---|---|---|---|---|---|
|
ADP |
3,000 |
2,500 |
2,000 |
500 |
1,000 |
935 |
2,000 |
11,905 |
Semester Fee
Semester fee Approximately Rs. 17000/-
Disclaimer
- The courses are regularly reviewed to ensure they are up-to-date with those taught at top universities, taking into account the needs of local industry and the job market.
- The University may change its fee structure from time to time.