Welcome to the BS Data Science program, where you will unlock the power of data-driven insights and chart your course towards an exciting career in the fast-evolving field of data science. Our four-year program is designed to equip you with a deep understanding of the technical and analytical skills necessary to extract meaningful insights from complex data sets, and translate those insights into actionable strategies for real-world problems’ solutions.
Our program offers a rigorous curriculum, covering a broad range of topics such as programming, statistics, machine learning, data visualization, and data ethics. You will learn to work with various data sources, use cutting-edge tools and techniques to transform raw data into valuable insights, and communicate your findings effectively to stakeholders.
Our distinguished faculty brings extensive industry experience, and will guide you through hands-on projects, individual research projects, and internships to help you develop a portfolio of work that demonstrates your ability to create impactful solutions.
Join us in the BS Data Science program to become a master of data and create solutions that make a real-world impact.
Graduates of our program will be well-equipped to pursue careers as data analysts, data scientists, machine learning engineers, and business intelligence analysts in a range of industries, such as healthcare, finance, technology, and consulting.
Data Science degree graduates can pursue a wide range of career opportunities across various industries. Some of the possible career opportunities after completing a BS Data Science degree program are:
Data Analyst: Analyzing data to identify trends, patterns, and insights and make recommendations based on the findings.
Data Scientist: Collecting and analyzing complex data to develop models and algorithms that can be used to make predictions and identify trends.
Business Analyst: Analyzing business processes and data to improve organizational efficiency and profitability.
Machine Learning Engineer: Developing and implementing machine learning models to enable computers to learn from data and improve their performance over time.
Data Engineer: Building and maintaining the infrastructure required to store, process, and analyze large datasets.
Database Administrator: Managing and maintaining the databases used to store and organize data for organizations.
Data Architect: Designing the overall structure of databases and data systems to ensure the efficient and effective use of data.
Data Visualization Developer: Creating interactive and dynamic data visualizations that enable stakeholders to explore data in a meaningful way.
Data Security Analyst: Ensuring that data is stored, processed, and transmitted securely to prevent data breaches and cyberattacks.
Data Governance Manager: Establishing and enforcing policies and procedures for data management to ensure data quality, privacy, and compliance with regulations.
Data Journalist: Analyzing and interpreting data to create data-driven news stories, articles, and reports.
Research Analyst: Collecting, analyzing, and interpreting data to support research projects in various fields such as social sciences, healthcare, and environmental studies.
Quantitative Analyst: Using statistical methods and mathematical models to analyze and interpret financial data in order to make investment decisions.
Risk Analyst: Identifying and analyzing potential risks and developing strategies to mitigate them for organizations.
Healthcare Data Analyst: Analyzing healthcare data to improve patient outcomes, reduce costs, and optimize healthcare delivery.
Program Distinctive Features
Hands-on experience with real-world data: BS Data Science programs offer opportunities for students to work with real-world datasets, giving them practical experience in data analysis and visualization.
Interdisciplinary coursework: Data Science programs often include courses in computer science, mathematics, statistics, and other disciplines to provide students with a well-rounded education.
Project-based learning: Data Science programs offer project-based learning opportunities, allowing students to apply their skills and knowledge to real-world problems.
Emphasis on data ethics and privacy: With increasing concerns about data privacy and ethics, some Data Science programs may focus on these issues and provide training in responsible data use.
Collaborative learning: Data Science programs may encourage collaborative learning through group projects and teamwork, reflecting the importance of collaboration in the field of data science.
Specialization options: Some Data Science programs may offer students the opportunity to specialize in a particular area, such as machine learning, data visualization, or big data.
Professional development opportunities: Data Science programs may offer workshops, seminars, and other professional development opportunities to help students prepare for careers in the field.
Global perspective: With the global nature of data science, some programs may offer coursework or opportunities for international study, providing students with a global perspective on data science.
Access to cutting-edge technology: Data Science programs may provide students with access to cutting-edge technology, software, and hardware used in data analysis and visualization.
Industry Advisory Committee: Industry Advisory Committee (IAC) and adjunct faculty from leading software houses to co teach and mentor students via supervising Final Year Projects.
ICT Facilities: State of art ICT facilities that includes high speed fiber optic internet connectivity and high-performance computing labs.
Market Support: Entrepreneurship support and software industry placement through annual job fairs.
Top Notch Faculty: A highly qualified faculty from top universities (national/international) and industry experts that impart unique blend of theoretical concepts and real-life problem-solving skills.
Four Years Bs Degree Program In Data Science: Total Credit Hours: 130
|#||Code||Pre-Reqs||Course Title||Domain||Cr hr|
|1||CS101||Programming Fundamentals||Core||4 (3-3)|
|2||GE101||Application of Information & Communication Technologies||GER||3 (2-3)|
|3||GE102||QR 1 (Discrete Structures)||GER||3 (3-0)|
|4||GE103||QR 2 (Calculus and Analytic Geometry)||GER||3 (3-0)|
|5||GE100||Functional English||GER||3 (3-0)|
|Total Cr Hrs||16 (14-6)|
|6||CS102||Programming Fundamentals||Object Oriented Programming||Core||4 (3-3)|
|7||CS111||Database Systems||Core||4 (3-3)|
|8||CS121||Digital Logic Design||Core||3 (2-3)|
|9||MT101||Multivariable Calculus||Maths||3 (3-0)|
|10||MT102||Linear Algebra||Maths||3 (3-0)|
|Total Cr Hrs||17 (14-9)|
|11||CS202||Object Oriented Programming||Data Structures||Core||4 (3-3)|
|12||CS231||Information Security||Core||3 (2-3)|
|13||CS241||Artificial Intelligence||Core||3 (2-3)|
|14||CS251||Computer Networks||Core||3 (2-3)|
|15||CS261||Software Engineering||Core||3 (3-0)|
|16||MT201||Probability & Statistics||Maths||3 (3-0)|
|Total Cr Hrs||19 (15-12)|
|17||CS222||Digital Logic Design||Computer Organization & Assembly Language||Core||3 (2-3)|
|18||CS271||Domain Core 1 (Introduction to Data Science)||Domain Core||3 (2-3)|
|19||CS272||Domain Core 2 (Advanced Statistics)||Domain Core||3 (2-3)|
|20||GE201||Natural Science (Applied Physics)||GER||3 (2-3)|
|21||GE104||Expository Writing||GER||3 (3-0)|
|22||GE202||Islamic Studies||GER||2 (2-0)|
|Total Cr Hrs||17 (13-12)|
|23||CS301||Operating Systems||Core||3 (2-3)|
|24||CS373||Domain Core 3 (Data Mining)||Domain Core||3 (2-3)|
|25||CS374||Domain Core 4 (Data Visualization)||Domain Core||3 (2-3)|
|26||CS311||Domain Elective 1||Domain Elective||3 (2-3)|
|27||CS312||Domain Elective 2||Domain Elective||3 (2-3)|
|28||GE202||Social Science (Example: Introduction to Management)||GER||2 (2-0)|
|Total Cr Hrs||17 (12-15)|
|29||CS375||Domain Core 5 (Data Warehousing & Business Intelligence)||Domain Core||3 (2-3)|
|30||CS376||Domain Core 6 (Parallel & Distributed Computing)||Domain Core||3 (2-3)|
|31||CS313||Domain Elective 3||Domain Elective||3 (2-3)|
|32||CS314||Domain Elective 4||Domain Elective||3 (2-3)|
|33||CS315||Domain Elective 5||Domain Elective||3 (2-3)|
|34||CS316||Domain Elective 6||Domain Elective||3 (2-3)|
|Total Cr Hrs||18 (12-18)|
|35||CS401||Final Year Project – I||Core||2 (0-6)|
|36||CS404||Data Structure||Analysis of Algorithms||Core||3 (3-0)|
|37||CS317||Domain Elective 7||Domain Elective||3 (2-3)|
|38||SS101||Elective Supporting Course (Example: Introduction to Marketing)||SS||3 (3-0)|
|39||EN401||Technical & Business Writing||EN||3 (3-0)|
|Total Cr Hrs||16 (13-9)|
|41||CS402||FYP-I||Final Year Project – II||Core||4 (0-12)|
|42||GE402||Ideology and Constitution of Pakistan||GER||2 (2-0)|
|43||GE403||Arts & Humanities (Professional Practices)||GER||2 (2-0)|
|44||GE404||Civics and Community Engagement||GER||2 (2-0)|
|Total Cr Hrs||10 (6-12)|