BS Data Science
ELIGIBILITY CRITERIA
The application fees in non-refundable (in any case) and Applicants seeking admission MUST MEET THE ELIGIBILITY REQUIREMENTS set-forth by Ziauddin University.
Data Science
The minimum requirements for admission in bachelor degree program in Data Science is any of following:
- a) At least 50% marks in Intermediate (HSSC) examination with Mathematics or equivalent qualification with Mathematics, certified by IBCC.
OR
- b) At least 50% marks in Intermediate (HSSC) examination with Pre-Medical or equivalent qualification, certified by IBCC.
Deficiency:
“Students with pre-medical, must have to pass deficiency courses of Mathematics of 6 credit hours in first two semesters.”
FEES STRUCTURE
| Tution fee/ credit | Exam fee / credit | No. of credit / sem | Tution fees | Exam fees | Semester registration fee | Activity fee / semester | Semester Fee |
| 3500 | 500 | 18 | 63000 | 9000 | 5000 | 2000 | 79000 |
** Tuition Fee and Exam Fee is calculated with Credit hours and will be changed in different Semesters
(e.g: Tuition Fee = 3500 x 18 = 63000 and Exam Fee = 500 x 18 = 9000)
| Semester Fee | Admission fee (One time Only) | Security Deposit (One time Only and Refundable) | Total 1st Semester fee |
| 79000 | 10000 | 5000 | 94,000 |
BS (Data Science-Evening) – Fee Structure For New Admission
| BS (Data Science) – Evening Fee Structure | Total Fee (pkr) |
| Admission Fee (One Time Only) | 15,000 |
| Security Deposit (One Time Only and Refundable) | 5,000 |
| Monthly (payable each month for the duration of studies) | 8500 |
| Total | 28,500/= |
Why Data Science?
- With a BS in Data Science, you will become the next generation analyst – a data scientist with comprehensive analytical and technical skills covering all aspects of handling and analyzing data.
- By deriving key insights from data you will be driving the decision-making of the future.
- You will learn to work in interdisciplinary teams and not only make sense of vast amounts of data, but also use your organizational knowledge and market understanding to make a difference.
Dedicated Lecture Rooms / Shared Lecture Room
- Adequacy of class rooms/lecture halls and allied facilities
- Average Size of each lecture rooms:
350 square feet
- Space Available for students:
30 square feet
- Instructional Facilities provided in lecture rooms:
White Board, Multimedia, Speaker system, Computer, Internet etc.
- Other facilities:
ACs
Laboratories
1) Computing Lab
| Lab Timings | Facilities |
| Weekdays (8:30am─4:30pm) | 32 workstations (core i3, core i5 3rd and 6th generations) installed with high end software. All workstations are connected with internet via LAN/Wi-Fi Access. Scanner and Printing Facility, white board and multimedia. Lab Space: 40 sq.ft per student |
- Operating System Lab
| Lab Timings | Facilities |
| Weekdays (8:30am─4:30pm) | 05 workstations (Core i3, Core i5 3rd and 6th generations) installed with high end software. All workstations are connected with internet via LAN/Wi-Fi Access. Printing Facility is also available. Lab Space: 40 sq.ft per student |
- Final year Project Lab
| Lab Timings | Facilities |
| Weekdays (8:30am─4:30pm) | 03 workstations (Core i3, Core i5 3rd and 6th generations) installed with high end software. All workstations are connected with internet via LAN/Wi-Fi Access. Printing Facility is also available.
|
Location:
- Address: North Campus (ZUFESTM), F-103, Block B, North Nazimabad,
- Karachi.
- Covered Areas (sq ft): 18000 sq ft (2000 sq yards) (Zufestm Area)
- Covered Areas (sq ft): 180 sq ft (SE Department Area)
- Building/Land Ownership, lease terms etc.
- Own Building
- Data Science is exponentially growing field these days especially after the evolution of 5G and IoT applications. The specialized human resource in this field is highly in demand.
- Since students will be exposed to cases and other pedagogical tools, as well as interact regularly with the corporate sector, graduates are expected to be absorbed in the value-addition sectors of Pakistan, including technology, food and beverages, transportation, telecom, automotive, and the health sectors.
- Data Science graduated will also be able to engage in start-up businesses pertaining to cloud services and data mining & management technologies.
Semester — I
| Sr.# | Course Code | Course Title | Th. | Lab | Cr. Hr |
| 1 | CS-107 | Introduction to Info. & Comm. Technologies | 2 | 1 | 2+1 |
| 2 | CS-104 | Programming Fundamentals | 3 | 1 | 3+1 |
| 3 | CS-103 | Discrete Structures | 3 | 0 | 3+0 |
| 4 | NS-115 | Basic Mathematics | 6 | 0 | N/C |
| 5 | NS-201 | Linear Algebra | 3 | 0 | 3+0 |
| 6 | HS-100 | English Composition & Comprehension | 3 | 0 | 3+0 |
| 7 | HS-103 | Pakistan Studies | 2 | 0 | 2+0 |
| Total | 16 | 2 | 18 | ||
Semester — II
| Sr.# | Course Code | Course Title | Th. | Lab | Cr.Hr |
| 1 | CS-112 | Object Oriented Programming | 3 | 1 | 3+1 |
| 2 | CS-233 | Introduction to Database System | 3 | 1 | 3+1 |
| 3 | NS-109 | Calculus and Analytical Geometry | 3 | 0 | 3+0 |
| 4 | NS-206 | Probability and Statistics | 3 | 0 | 3+0 |
| 5 | HS-114 | Communication & Presentation Skills | 3 | 0 | 3+0 |
| Total | 15 | 2 | 17 | ||
Semester — III
| Sr.# | Course Code | Course Title | Th. | Lab | Cr .Hr |
| 1 | CS-211 | Data Structures and Algorithms | 3 | 1 | 3+1 |
| 2 | CS-214 | Computer Org. & Assembly Language | 3 | 1 | 3+1 |
| 3 | CS-227 | Introduction to Data Science | 2 | 1 | 2+1 |
| 4 | EE-212 | Digital Logic Design | 3 | 1 | 3+1 |
| 5 | NS-112 | Differential Equations | 3 | 0 | 3+0 |
| Total | 14 | 4 | 18 | ||
Semester — IV
| Sr.# | Course Code | Course Title | Th. | Lab | Cr.Hr |
| 1 | CS-355 | Computer Communication and Networks | 3 | 1 | 3+1 |
| 2 | CS-351 | Automata Theory and Formal Language (DS Elective-1) | 3 | 0 | 3+0 |
| 3 | CS-226 | Analysis of Algorithms | 3 | 0 | 3+0 |
| 4 | CS-213 | Artificial Intelligence | 3 | 1 | 3+1 |
| 5 | NS-211 | Advance Statistics | 3 | 0 | 3+0 |
| Total | 15 | 2 | 17 | ||
Semester — V
| Sr.# | Course Code | Course Title | Th. | Lab | Cr.Hr |
| 1 | CS-234 | Operating Systems | 3 | 1 | 3+1 |
| 2 | CS-336 | Data Mining | 2 | 1 | 2+1 |
| 3 | CS-331 | Data Warehousing & Business Intel. | 2 | 1 | 2+1 |
| 4 | CS-355 | Machine Learning (DS Elective-2) | 2 | 1 | 2+1 |
| 5 | MS-306 | Managerial Economics (University Elective-1) | 3 | 0 | 3+0 |
| Total | 12 | 4 | 16 | ||
Semester — VI
| Sr.# | Course Code | Course Title | Th. | Lab | Cr.Hr |
| 1 | C-332 | Parallel & Distributed Computing | 2 | 1 | 2+1 |
| 2 | CS-456 | Big Data Analytics | 2 | 1 | 2+1 |
| 3 | CS-333 | Data Visualization | 2 | 1 | 2+1 |
| 4 | CS-352 | Digital Image Processing (DS Elective 3) | 3 | 0 | 3+0 |
| 5 | CS-454 | Cloud Computing (DS Elective-4) | 2 | 1 | 2+1 |
| 6 | MS-203 | Human Resource Management (University Elective-3) | 3 | 0 | 3+0 |
| Total | 14 | 4 | 18 | ||
Semester — VII
| Sr.# | Course Code | Course Title | Th. | Lab | Cr.Hr |
| 1 | DS-451 | Final Year Project –I | 0 | 3 | 0+3 |
| 2 | CS-212 | Introduction to Software Engineering | 2 | 1 | 2+1 |
| 3 | MS-414 | Entrepreneurship and Leadership (University Elective-2) | 3 | 0 | 3+0 |
| 4 | HS-331 | Technical and Business Writing | 3 | 0 | 3+0 |
| 5 | HS-100 HS-102
| Islamic Studies / Ethical Behavior | 2 | 0 | 2+0 |
| Total | 10 | 4 | 14 | ||
Semester — VIII
| Sr.# | Course Code | Course Title | Th. | Lab | Cr.Hr |
| 1 | DS-451 | Final Year Project –II | 0 | 3 | 0+3 |
| 2 | HS-107 | Psychology (University Elective-4) | 3 | 0 | 3+0 |
| 3 | HS-401 | Professional Practices | 3 | 0 | 3+0 |
| 4 | CS-304 | Information Security | 3 | 0 | 3+0 |
| Total | 9 | 3 | 12 | ||
| Total Credit Hours | 130 |
| Total Lab Credit Hours | 25 |
| Total Theory Credit Hours | 105 |