Introduction
In an era where data is the new oil, the ability to analyze and derive insights from vast amounts of information is a skill in high demand. The Associate Degree in Data Science is designed to equip students with the foundational knowledge and practical skills needed to navigate and excel in the dynamic world of data. By blending rigorous academic coursework with hands-on experience, this program prepares students to meet the challenges of data-driven decision-making in various industries, including business, healthcare, finance, and technology.
Our comprehensive curriculum covers essential areas such as programming, data analysis, machine learning techniques, and data visualization, ensuring that graduates are well-versed in the latest tools and techniques. Beyond technical proficiency, the program emphasizes critical thinking, ethical responsibility, and effective communication, fostering well-rounded professionals ready to lead in multidisciplinary teams. Graduates will unlock the potential of data and drive innovation in their chosen field, setting a solid foundation for a successful career in data sciene.
Eligibility Criteria
- Minimum 50% marks in Intermediate/12 years schooling/A- Level (HSSC) or Equivalent with Mathematics are required for admission in Associate Degree in Data Science. 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 (06 credits) in first two semesters.
- “Zero Semester” is not applicable.
Award of Degree
To be eligible for the award of Associate Degree Program in Data Science, a student is required to complete at least 72 credit hours with minimum Cumulative Grade Point Average of 2.00 out of 4.00.
Scheme of Study
| Total Credit Hours | 72 |
| Total Semesters | 4 |
| Duration | 2 years |
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| Semester No. 1 | |||||||||
| Course Code | Title | Category | Sub Category | Type | Pre Requisite | Credit Hours | Specialization | ||
| CS101 | Introduction to Computing | General Education | Applications of Information and Communication Technologies (ICT) | Required | 3 (Theory:3, Practical:0) | ||||
| ENG101 | English Comprehension | General Education | Functional English | Required | 3 (Theory:3, Practical:0) | ||||
| MGT602 | Entrepreneurship | General Education | Entrepreneurship | Required | 3 (Theory:3, Practical:0) | ||||
| MTH202 | Discrete Mathematics | General Education | Quantitative Reasoning | Required | 3 (Theory:3, Practical:0) | ||||
| MTH501 | Linear Algebra | General Education | Quantitative Reasoning | Required | 3 (Theory:3, Practical:0) | ||||
| MTH100 | General Mathematics | Interdisciplinary | Mathematics Supporting | Deficiency | 3 (Theory:3, Practical:0) | ||||
| ETH202 | Ethics (for Non-Muslims) | General Education | Islamic Studies/Religious Education Studies | Elective | 2 (Theory:2, Practical:0) | ||||
| ISL202 | Islamic Studies | General Education | Islamic Studies/Religious Education Studies | Elective | 2 (Theory:2, Practical:0) | ||||
| VU001 | Introduction to e-Learning | Interdisciplinary | Required | 1 (Theory:1, Practical:0) | |||||
| Semester No. 2 | |||||||||
| Course Code | Title | Category | Sub Category | Type | Pre Requisite | Credit Hours | Specialization | ||
| CS205 | Information Security | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| CS306 | Introduction to Python | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| CS442 | Introduction to Data Science | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| ENG201 | Business and Technical English Writing | General Education | Expository Writing | Required | 3 (Theory:3, Practical:0) | ||||
| STA301 | Statistics and Probability | General Education | Quantitative Reasoning | Required | 3 (Theory:3, Practical:0) | ||||
| MTH104 | Sets and Logic | Interdisciplinary | Mathematics Supporting | Deficiency | 3 (Theory:3, Practical:0) | ||||
| PAK301 | Pakistan Studies | General Education | Ideology and Constitution of Pakistan | Required | 2 (Theory:2, Practical:0) | ||||
| CS306P | Introduction to Python (Practical) | Major | Computing Core | Required | 1 (Theory:0, Practical:1) | ||||
| Semester No. 3 | |||||||||
| Course Code | Title | Category | Sub Category | Type | Pre Requisite | Credit Hours | Specialization | ||
| CS403 | Database Management Systems | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| CS628 | Machine Learning | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| STA302 | Data Analytics and Business Intelligence | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| STA621 | Time Series Analysis | Major | Domain Electives | Required | 3 (Theory:3, Practical:0) | ||||
| CS435 | Cloud Computing | Major | Domain Electives | Elective | 3 (Theory:3, Practical:0) | ||||
| CS441 | Big Data Concepts | Major | Domain Electives | Elective | 3 (Theory:3, Practical:0) | ||||
| CS514 | Internet of Things (IoT) | Major | Domain Electives | Elective | 3 (Theory:3, Practical:0) | ||||
| CS641 | Big Data Analytics | Major | Domain Electives | Elective | 3 (Theory:3, Practical:0) | ||||
| Semester No. 4 | |||||||||
| Course Code | Title | Category | Sub Category | Type | Pre Requisite | Credit Hours | Specialization | ||
| CS513 | Advanced Data Analytics and Business Intelligence | Major | Domain Electives | Required | 3 (Theory:3, Practical:0) | ||||
| CS519 | Final Project | Major | Capstone Project | Required | 3 (Theory:3, Practical:0) | ||||
| CS614 | Data Warehousing | Major | Domain Electives | Required | 3 (Theory:3, Practical:0) | ||||
| CS620 | Modelling and Simulation | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| CS626 | Data Mining Techniques | Major | Computing Core | Required | 3 (Theory:3, Practical:0) | ||||
| CS631 | Deep Learning | Major | Domain Electives | Required | 3 (Theory:3, Practical:0) | ||||