BS (Data Science) has a dual emphasis on basic principles of statistics and computer science, with foundational training in statistical and mathematical aspects of data analysis. This program, in addition, develops foundation on broad computer science principles, including algorithms, data structures, data management and machine learning. The program is suitable for students interested in either a career in industry or who wish to pursue more specialized graduate study. This program  will prepare students for a career in data analysis, combining foundational statistical concepts with computational principles from computer science. A major component of this degree is the final year two-semester project, that teaches students how to apply statistical and computational principles to solve large-scale, real-world data analysis problems. BS (Data Science) is a four year degree program. It requires completion of 144 credit hours of course work and 2 credit hours of internship of at least six weeks at an organization approved by the Institute.

Data Science students learn to:

  • Define information needs of individuals and organizations; 
  • Select and transform data to increase usefulness for solving particular problems; 
  • Analyze and synthesize unstructured data to create actionable information; 
  • Create information visualizations for data exploration and presentation; 
  • Manage very large volume data sources from acquisition through disposal; 
  • Secure and preserve data in ways consistent with legal and organizational considerations

Learning Outcomes for Data Science Certificate students include:

  1. Knowledge of how to apply analytic techniques and algorithms (including statistical and data mining approaches) to large data sets to extract meaningful insights.
  2. Acquisition of hands-on experience with relevant software tools, languages, data models, and environments for data processing and visualization.
  3. Ability to communicate results of analysis effectively (visually and verbally) to a broad audience.

Required Courses

Area  Course Code/Title
Accounting ACC101 Introduction to Financial Accounting
Communication COM107 Academic English
COM202 Business and Professional Speech
COM205 Persuasive & Analytical Writing for Bus. Com
Economics ECO104 Micro and Macroeconomics
ECO304 Introduction to Econometrics
Language LAN 10* Foreign Language I
*1 = Introduction to Arabic
*2 = Introduction to French
*4 = Introduction to German
*6 = Introduction to Italian
*8 = Introduction to Chinese
Management MAN101 Principles of Management
MAN411 Project Management
Data Science BDS101 Introduction to Data Science
BDS201 Business Process Analysis
BDS301 Data Mining-I
BDS302 Data Mining -II
BDS401 Data Visualization
BDS402 Big Data Concept & Techniques
BDS403 Big Data & Analytics
BDS404 Machine Learning
Mathematics MTH107 Calculus and Analytical Geometry
MTH204 Linear Algebra
MTH215 Differential Equations
MTH222 Discrete Structures
MTH224 Multivariable Calculus
MTH405 Numerical Analysis
Computer Science CSC105 Data Structures and Algorithms
CSC111 Intro. to Information & Communication Technology
CSC112 Object Oriented Programming
CSC113 Programming Fundamentals
CSC205 Computer Architecture
CSC217 Digital Logic Design
CSC220 Introduction to Database Management Systems
CSC315 Theory of Automata and Formal Language
CSC317 Introduction to Software Engineering
CSC318 Design & Analysis of Algorithms
CSC410 Data Communication and Networking
CSC412 Artificial Intelligence
CSC428 Web Engineering
CSC443 Mobile Computing
CSC445 Network Security
CSC461 Project I
CSC462 Project II
CSC463 Introduction to Data Warehousing
Statistics STA203 Probability Theory & Statistics I
STA204 Probability Theory & Statistics II
STA301 Model & Inference
STA302 Methods of Data Analysis
STA305 Applied Regression Analysis
STA303 Time Series Analysis
Religious Studies REL101 Islamic Studies
Political Sciences PSC301 Pakistan Studies



Course Structure

Semester One Semester Two Semester Three Semester Four
Introduction to Data Science
Programming Fundamentals (2+1)
Probability theory & Statistics I
Calculus and Analytical Geometry
Islamic Studies
Academic English
Multivariable Calculus
Object Oriented Programming (2+1)
Probability Theory & Statistics II
Persuasive & Analytical Writing for Bus. Com.
Discrete Structures
Pakistan Studies
Linear Algebra
Intro. to Info. & Comm. Tech. (2+1)
Model & Inference
Business & Professional Speech OR Foreign Language I
Data Structures and Algorithms (2+1)
Micro and Macroeconomics
Differential Equations
Computer Architecture & Organization (2+1)
Methods of Data Analysis
Business Process Analysis
Data Communication and Networking (2+1)
Intro. to Database Management Systems
Semester Five Semester Six Semester Seven Semester Eight
Numerical Computing (2+1)
Data Mining -I
Applied Regression Analysis
Intro. to Software Engineering (2+1)
Mobile Computing
Theory of Automata & Formal Language
Principles of Management
Introduction to Econometrics
Data Mining -II
Design & Analysis of Algorithms (2+1)
Artificial Intelligence
Network Security
Data Visualization
Digital Logic Design (2+1)
Time Series Analysis
Project I
Big Data Concept & Techniques Introduction to Financial Accounting
Project II
Introduction to Data Warehousing
Big Data & Analytics
Project Management
Machine Learning (2+1)
Web Engineering (2+1)