Bachelor of Science in Data Science (BSDS)

Program introduction

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.

Program Objectives

  1. Develop proficiency in programming languages used in data science, such as Python and R.
  2. Develop strong mathematical and statistical skills to analyze data and draw insights from data.
  3. Learn to use data visualization tools and techniques to communicate insights effectively.
  4. Understand the principles of machine learning and artificial intelligence and how they can be applied in data science.
  5. Acquire knowledge of big data technologies and platforms for managing and processing large datasets.
  6. Develop an understanding of data ethics and privacy issues in data science.
  7. Learn to work with unstructured data such as text, images, and videos.
  8. Develop skills in data preparation, cleaning, and transformation.
  9. Understand data governance and quality assurance practices.
  10. Learn to collaborate effectively in interdisciplinary teams on data science projects.


Career Opportunities

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

#CodePre-ReqsCourse TitleDomainCr hr
Semester 1
1CS101 Programming FundamentalsCore4 (3-3)
2GE101 Application of Information & Communication TechnologiesGER3 (2-3)
3GE102 QR 1 (Discrete Structures)GER3 (3-0)
4GE103 QR 2  (Calculus and Analytic Geometry)GER3 (3-0)
5GE100 Functional EnglishGER3 (3-0)
    Total Cr Hrs16 (14-6)
Semester 2
6CS102Programming FundamentalsObject Oriented ProgrammingCore4 (3-3)
7CS111 Database SystemsCore4 (3-3)
8CS121 Digital Logic DesignCore3 (2-3)
9MT101 Multivariable CalculusMaths3 (3-0)
10MT102 Linear AlgebraMaths3 (3-0)
    Total Cr Hrs17 (14-9)
Semester 3
11CS202Object Oriented ProgrammingData StructuresCore4 (3-3)
12CS231 Information SecurityCore3 (2-3)
13CS241 Artificial IntelligenceCore3 (2-3)
14CS251 Computer NetworksCore3 (2-3)
15CS261 Software EngineeringCore3 (3-0)
16MT201 Probability & StatisticsMaths3 (3-0)
    Total Cr Hrs19 (15-12)
Semester 4
17CS222Digital Logic DesignComputer Organization & Assembly LanguageCore3 (2-3)
18CS271 Domain Core 1 (Introduction to Data Science)Domain Core3 (2-3)
19CS272 Domain Core 2 (Advanced Statistics)Domain Core3 (2-3)
20GE201 Natural Science (Applied Physics)GER3 (2-3)
21GE104 Expository WritingGER3 (3-0)
22GE202 Islamic StudiesGER2 (2-0)
    Total Cr Hrs17 (13-12)
Semester 5
23CS301 Operating SystemsCore3 (2-3)
24CS373 Domain Core 3 (Data Mining)Domain Core3 (2-3)
25CS374 Domain Core 4 (Data Visualization)Domain Core3 (2-3)
26CS311 Domain Elective 1Domain Elective3 (2-3)
27CS312 Domain Elective 2Domain Elective3 (2-3)
28GE202 Social Science (Example: Introduction to Management)GER2 (2-0)
    Total Cr Hrs17 (12-15)
Semester 6
29CS375 Domain Core 5 (Data Warehousing & Business Intelligence)Domain Core3 (2-3)
30CS376 Domain Core 6 (Parallel & Distributed Computing)Domain Core3 (2-3)
31CS313 Domain Elective 3Domain Elective3 (2-3)
32CS314 Domain Elective 4Domain Elective3 (2-3)
33CS315 Domain Elective 5Domain Elective3 (2-3)
34CS316 Domain Elective 6Domain Elective3 (2-3)
    Total Cr Hrs18 (12-18)
Semester 7
35CS401 Final Year Project – ICore2 (0-6)
36CS404Data StructureAnalysis of AlgorithmsCore3 (3-0)
37CS317 Domain Elective 7Domain Elective3 (2-3)
38SS101 Elective Supporting Course (Example: Introduction to Marketing)SS3 (3-0)
39EN401 Technical & Business WritingEN3 (3-0)
40GE401 EntrepreneurshipGER2 (2-0)
    Total Cr Hrs16 (13-9)
Semester 8
41CS402FYP-IFinal Year Project – IICore4 (0-12)
42GE402 Ideology and Constitution of PakistanGER2 (2-0)
43GE403 Arts & Humanities (Professional Practices)GER2 (2-0)
44GE404 Civics and Community EngagementGER2 (2-0)
    Total Cr Hrs10 (6-12)
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