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
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 at ZU?
“Ziauddin University Data Science degree program provides students with the technical skills, analytical knowledge, and practical experience necessary to succeed in the growing field of Data Sscience”.
Salient Features of the Data Science program offered at Ziauddin University:
- In-depth knowledge of data analysis techniques: A data science curriculum is very well designed that covers the essential topics as per academia and modern industry requirements. A data science curriculum provides students with a deep understanding of data analysis techniques such as statistical analysis, data mining, data Visualization, machine learning and Database Systems. This knowledge is essential for making sense of large and complex data sets.
- Proficiency in programming: Data scientists use programming languages such as Python, R, and SQL to manipulate, clean, and analyse data. A data science degree program of Ziauddin University teaches students the programming skills necessary for these tasks.
- Understanding of database systems: Data is stored in various formats and systems, including relational databases, NoSQL databases, and data warehouses. A data science degree program teaches students how to interact with these systems, manipulate data, and extract useful insights.
- Communication skills: Data scientists work with various stakeholders, including business leaders, developers, and other data professionals. A data science degree program teaches students how to effectively communicate data insights to different audiences.
- Computing resources: Data science program at Ziauddin University offers significant computing resources to process and analyze large data sets. This includes access to high-performance computing clusters, cloud computing platforms, and specialized hardware such as graphics processing units (GPUs).
- Software tools: For students of Data Science a wide range of software tools to analyze data, including programming languages such as Python and R, and data analysis tools such as SQL, Tableau, and Excel are available. These Software tools are available for students to access them in various courses.
- Faculty: Ziauddin University is famous for experienced and knowledgeable faculty members with expertise in data science. Our faculty members have a strong background in statistics, computer science, and data analysis, as well as experience working in industry.
- Laboratories: Data science program have laboratories equipped with computing resources, software tools, and data sets. These laboratories are accessible to students outside of class hours to enable them to work on projects and assignments.
Data science is a rapidly growing field with a wide range of career opportunities. Here are some popular career paths in data science:
- Data scientist: A data scientist is responsible for collecting, processing, and analyzing large data sets using statistical methods and machine learning techniques. Data scientists use their knowledge to provide insights and recommendations to business leaders and other stakeholders.
- Data analyst: A data analyst is responsible for collecting, cleaning, and analyzing data to provide insights and recommendations. Data analysts typically work with smaller data sets and use basic statistical techniques to find patterns and trends in the data.
- Machine Learning Engineer: A machine learning engineer is responsible for developing and implementing machine learning algorithms to solve specific business problems. Machine learning engineers need to have a strong background in computer science, statistics, and machine learning.
- Business Intelligence Analyst: A business intelligence analyst is responsible for collecting and analyzing data to help business leaders make informed decisions. Business intelligence analysts use data visualization tools and other techniques to create dashboards and reports that provide insights into key business metrics.
- Data Engineer: A data engineer is responsible for building and maintaining the infrastructure that supports data analysis. Data engineers design and implement databases, data pipelines, and other systems to manage and process large data sets.
- Big Data Analyst: A big data analyst is responsible for analyzing large and complex data sets using tools such as Hadoop and Spark. Big data analysts use their expertise to identify patterns and trends in the data that can be used to make informed business decisions.
In summary, data science offers a wide range of career opportunities, including data scientist, data analyst, machine learning engineer, business intelligence analyst, data engineer, and big data analyst. As data continues to play a crucial role in business decision-making, the demand for skilled data professionals is expected to continue to grow in the coming years.
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 |