BS Data
Science

Department

Computer Science

Level

Undergraduate

College

College of Computer Sciences & Information Systems

Program Detail

BS (Data Science) focuses on statistical analysis and theoretical computer science to develop solutions that employ robust mathematical models. These models help AI (Artificial Intelligence) and other predictive tools for data mining and reliable analysis.

This program has a twofold approach: basic principles and foundational training of statistical and mathematical aspects of data analysis. This program is, additionally, based on broad computer science principles, including algorithms, data structures, data management, and machine learning. The program is suitable for students interested either in a career in industry or 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 Data Science principles for solving large-scale, real-world data analysis problems BS (Data Science) is a four-year degree program. It requires completion of 138+2* credit hours of coursework and compulsory internship (3 credit hours) of at least six weeks at an organization ap-proved by the Institute.

 

Students from pre-medical background are required to additionally complete the following two mathematics courses: MAT011 Basic College Mathematics

MAT012 Intermediate College Mathematics

 

Eligibility Criteria: The eligibiliity criteria for admission into BS Data Science is given on Page No. 175.

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

1.      Data Architect

2.

Infrastructure Architect

3.      Data Scientist

4.

Data Analyst

5.      Data Engineer

6.

Machine Learning Engineer & Architect

 

1.      Real Estate Industry

2.

Hospital Industry

3.      Social Media Data Analytics Firms

4.

Food and Supply Industry

5.      Banking Sector

6.

Airline Industry

7.      Communication & Transportation Industry

8.

Government & Private Sector

9.      Insurance Industry

 

 

Area

Credit Hours

Courses

Computing Core [CC]

49

14

Domain Core [DC]

18

6

Domain Elective [DE]

21

7

Mathematics & Supporting Courses [MSC]

12

4

Elective Supporting Courses [ESC]

3

1

General Education Requirements [GER]

31

13

Professional Certification

3

1

Internship

3

1

Total

140*

48*

Note for Non-Muslim Students

Non-Muslim students will take a suitable 2-credit-hour General Education course in place of Understanding of the Holy Quran, as approved by the Institute’s statutory bodies.

A nine-hour non-credit ‘Pre-sessional Intensive English module’ is mandatory for freshmen who scored below 50% in the English portion of the IOBM admission test. This nine-hour pre-sessional course is conducted one week before the start of the Semester.

Semester I

 

Course Code

Course Name

Credit Hours

Pre-requisite

CSP111 CSP111

Introduction to Information & Communication Technology [GER] Introduction to Information & Communication Technology Lab

2+0

0+1

–

CSP121 CSP121

Programming Fundamentals [CC] Programming Fundamentals Lab

3+0

0+1

–

BCN101

Academic English [GER]

3+0

–

PHY112 PHY112

Applied Physics [GER] Applied Physics Lab

2+0

0+1

–

MAT110

Calculus and Analytical Geometry [GER]

3+0

–

 

Semester Total Credit Hours

16 (13+3)

 

 

Semester II

 

Course Code

Course Name

Credit Hours

Pre-requisite

CSP122 CSP122

Object Oriented Programming [CC] Object Oriented Programming Lab

3+0

0+1

CSP121

BCN201

Persuasive & Analytical Writing for Business Communication [MSC]

3+0

BCN101

CSP231

Discrete Structure [GER]

3+0

–

CSP141 CSP141

Digital Logic and Design [CC] Digital Logic and Design Lab

3+0

0+1

PHY112

MAT211

Multivariable Calculus [MSC]

3+0

MAT110

REL102/

REL112

Understanding of Holy Quran-I [GEC] /

Comparative Religion-I [GEC]

0+1

0+1

–

 

Semester Total Credit Hours

18 (16+2)

 
Semester III

 

Course Code

Course Name

Credit Hours

Pre-requisite

CSP221 CSP221L

Data Structures and Algorithms [CC] Data Structures and Algorithms Lab

3+0

0+1

CSP121

BCN202

Business and Professional Speech [GER]

3+0

COM107

CSP241 CSP241

Comp. Organization & Assembly Lang. [CC] Comp. Organization & Assembly Lang. Lab

3+0

0+1

–

MAT201

Linear Algebra [MSC]

3+0

MAT110

REL101

Islamic Studies [GER]

2+0

–

REL103/

REL113

Understanding of Holy Quran-II [GEC] /

Comparative Religion-I GEC

0+1

0+1

REL102/

REL112

 

Semester Total Credit Hours

17 (15+2)

 

 

Semester IV

 

Course Code

Course Name

Credit Hours

Pre-requisite

CSP261 CSP261

Introduction to Database Systems [CC] Introduction to Database Systems Lab

3+0

0+1

–

DSP162 DSP162

Introduction to Data Science [DC] Introduction to Data Science Lab

2+0

0+1

–

STS101

Probability Theory and Statistics [MSC]

3+0

–

CSP222 CSP222

Operating Systems [CC] Operating Systems Lab

3+0

0+1

CSP221

CSP228

Design & Analysis of Algorithms [CC]

3+0

CSP221

 

Semester Total Credit Hours

17 (14+3)

 

 

Semester V

 

Course Code

Course Name

Credit Hours

Pre-requisite

DSP365 DSP365

Advanced Statistics [DC] Advanced Statistics Lab

2+0

0+1

STS101

CSP371 CSP371

Computer Networks [CC] Computer Networks Lab

2+0

0+1

–

MGT102

Introduction to Management & Organizational Behavior [GER]

2+0

–

CSP311

Professional Practices [GER]

2+0

> 60 Credit Hours

DSP366 DSP366

Data Mining [DC] Data Mining Lab

2+0

0+1

–

CSP381 CSP381

Artificial Intelligence [CC] Artificial Intelligence Lab

2+0

0+1

STA203

PSC101

Pakistan Studies [GER]

2+0

 
 

Semester Total Credit Hours

18 (15+3)

 
Semester VI

Course Code

Course Name

Credit Hours

Pre-requisite

DSPxxx

DS Elective 1 [DE]

3+0

–

DSPxxx

DS Elective 2 [DE]

3+0

–

SEP151

Introduction to Software Engineering [CC]

3+0

–

DSP368 DSP368

Data Visualization [DC] Data Visualization Lab

2+0

0+1

–

DSP367 DSP367

Data Warehouse and Business Intelligence [DC] Data Warehouse and Business Intelligence Lab

2+0

0+1

–

CSP313

Tech Entrepreneurship [GER]

2+0

–

 

Semester Total Credit Hours

17 (15+2#)

 
Semester VII

Course Code

Course Name

Credit Hours

Pre-requisite

DSPxxx

DS Elective 3 [DE]

3+0

–

DSPxxx

DS Elective 4 [DE]

3+0

–

MRK101

Fundamentals of Marketing Management [ESC]

3+0

–

SSC303

Service Learning and Civic Responsibilities [GER]

2+0

–

CSP443

Parallel and Distributed Computing [DC]

3+0

CSP222 & CSP371

  DSPxxx

Professional Certification

3+0

–

DSP491

Final Year Project I [CC]

0+3

–

 

Semester Total Credit Hours

20 (17+3#)

 
Semester VIII

Course Code

Course Name

Credit Hours

Pre-requisite

DSPxxx

DS Elective 5 [DE]

3+0

 

DSPxxx

DS Elective 6 new [DE]

3+0

 

DSPxxx

DS Elective 7 new [DE]

3+0

 

CSP472

Information Security [CC]

3+0

 

PSC302

Ideology and Constitution of Pakistan [GER]

2+0

 

DSP492

Final Year Project II [CC]

0+3

DSP491

 

Semester Total Credit Hours

17 (14+3#)

 

Total 138 Credit Hours (#Lab depends on the selection of elective courses by students)

DSPxxx Large Language Models

DSP468 Social Network Analysis

DSP481 Machine Learning

DSP462 Information Extraction

DSP483 Artificial Neural Networks

CSP331 Theory of Automata & Formal Lang.

DSP465 Information Retrieval

DSP485 Deep Learning

DSP461 Platform & Architecture for Data Science

CSP325 HCI and Computer Graphics CSP325 HCI and Computer Graphics Lab

DSP464 Speech Processing

DSP467 Big Data Analytics

CSP362 Advanced Database Systems CSP362 Advanced Database Systems Lab

DSP463 Natural Language Processing

DSP469 Topics in Data Science

CSP479 Cloud Computing

Course Detail

BS (Mathematics & Economics) is an inter-disciplinary undergraduate program for students with robust mathematical skills and keen interest in economics. This program is a perfect blend of pure and applied mathematics which does not only ensure a solid quantitative foundation for both disciplines but also provide phenomenal coverage of Statistics, Actuarial sciences and Finance. The training this degree provides is a unification of critical economic analysis and strong mathematical skills, which can help student pursue an esteemed position in financial services industry, growth and development centers, business enterprises, as well as public sector. Graduates with this degree are increasingly valued by employers because of their critical reasoning and sound knowledge as much of the economic theory is currently presented in terms of mathematical models. This opens more career options than the ones traditionally available to either mathematics or economics majors. This degree is also a paragon for those who aim for Master/ Doctoral degree in Economics, Finance, Mathematics, Statistics, Actuarial Sciences or other related fields. 

The BS (Mathematics & Economics) is a four-year program. Applicants who have successfully completed H.Sc with minimum 50% marks in Pre-Engineering or in General Group (with Mathematics) or A-Levels with a minimum 2 Cs in three principal subjects (with Mathematics) are eligible to apply for admission. Graduation requirement is the completion of 141 credit hours of course work and 3 credit hours of project approved by college. Students must take a minimum load of 12 credit hours (four courses) or a maximum load of 18 credit hours (six courses) in a semester. In order to obtain the BS degree in four years, a student is required to cover twelve courses in a year. Full load of six courses can be taken each in the Fall and Spring semesters with an option of four courses in the latter and making up for the short fall in summer session. Students must maintain a CGPA of 2.5 for the conferment of degree.

BS Mathematics and Economics students learn to:

  • An ability to develop mathematical thinking, evolving from a computational / procedural understanding of mathematics to a broad understanding that involves logical reasoning, generalization, inference and formal proof.

  • Learn the fundamental aspects of economics, formulation and use of quantitative models arising in social science, business and other contexts.

  • Acquire an understanding of basic pure mathematics, and of the role of logical argument in mathematics.

  • Learn to use basic econometric methods to quantify uncertainty with confidence intervals; use regression to infer causal relationships; and use regressions for prediction

Learning Outcomes for Business Analytics Students include:

  1. An ability to communicate effectively with the educational and business community and with society at large about mathematical and economical principles, concepts, and solution to problems with precision and adherence in written, oral and graphical form about concrete questions and to prepare well-organized written arguments that clearly state assumptions/ hypotheses supported by evidence.

  2. An ability to optimally apply economic analysis to everyday economic problems in the real world. This shall allow them to understand current events and evaluate potential policy proposals. Moreover, an appreciation shall be developed to evaluate the role played by assumptions in situations that reach various conclusions to a specific economic or policy problem.

  3. Be equipped with skills to apply optimization models to consumer, producer, and market theories and to use game theory to analyze the strategic behavior of individuals and firms.

  4. Be equipped with the investigative skills necessary for conducting original economic research and participating effectively in project teams.

  • Data analyst

  • Investment analyst

  • Research scientist

  • Statistician

Area Course Code/Title
MathematicsMTH104 Calculus I
MTH105 Calculus II
MTH203 Introduction to Formal Mathematics
MTH204 Linear Algebra
MTH213 Introduction to Computing
MTH224 Multivariable Calculus
MTH251 Number theory
MTH301 Real Analysis I
MTH311 Real Analysis II
MTH344 Introduction to Differential Equations
MTH346 Partial Differential Equations
MTH350 Topics in Mathematical Economics
MTH405 Numerical Analysis
MTH427 Topology
MTH401 Complex Analysis
MTH433 Optimization Techniques
MTH437 Functional Analysis
EconomicsECO101 Principles of Microeconomics
ECO102 Principles of Macroeconomics
ECO103 Intermediate Microeconomics
ECO105 Intermediate Macroeconomics
ECO207 Game Theory
ECO208 Development Economics
ECO301 Managerial Economics
ECO302 International Trade
ECO303 Financial Economics
ECO307 Monetary theory and Policy
ECO402 Pakistan Economic Policy
ECO410 Econometrics I
ECO412 Econometrics II
Management Information SystemMIS402 Computer Concepts and Applications
Political SciencesPSC301 Pakistan Studies
Religious StudiesREL101 Islamic Studies
StatisticsSTA203 Probability Theory and Statistics
STA301 Model and Inference
STA302 Methods of Data Analysis
STA303 Time Series Analysis
STA305 Applied Regression Analysis
CommunicationCOM107 Academic English
COM202 Business and Professional Speech
COM203 Methods in Business Writing
LanguageLAN 10* Foreign Language I
LAN 20** Foreign Language II
*1 = Introduction to Arabic
*2 = Introduction to French
*4 = Introduction to German
*6 = Introduction to Italian
*8 = Introduction to Chinese
**1 = Intermediate Arabic
**2 = Intermediate French
**4 = Intermediate German
**6 = Intermediate Italian
**8 = Intermediate Chinese
Area Course Code/Title
MathematicsMTH211 Actuarial Mathematics
MTH205 Financial Mathematics
MTH207 Stochastic Models and Mathematical Finance
MTH421 Abstract Algebra
MTH423 Combinatorics
MTH430 Operations Research
MTH439 Introduction to Dynamical Systems
EconomicsECO305 Topics in Microeconomics
ECO306 Topics in Macroeconomics
ECO414 Islamic Economics
ECO416 Growth Theories
ECO418 Resource & Environmental Economics
ECOXXX Energy Economics
ECOXXX Public Finance
ECOXXX Economics of Logistics
ECOXXX History of Economics Idea
ECOXXX Agronomics
Semester OneSemester TwoSemester ThreeSemester Four
Islamic studies
Academic English
Principles of Microeconomics
Calculus I
Foreign Language I
Computer concepts and applications
Pakistan Studies
Methods in Business Writing
Principles of Macroeconomics
Calculus II
Foreign Language II
Probability & Statistics
Business and Professional Speech
Intermediate Microeconomics
Model and inference
Introduction to Formal Mathematics
Multi variable Calculus
Introduction to Computing
Intermediate Macroeconomics
Development Economics
Game Theory
Methods of Data Analysis
Number theory
Linear Algebra
Semester FiveSemester SixSemester SevenSemester Eight
International Trade
Managerial Economics
Applied Regression Analysis
Topics in Mathematical Economics
Real Analysis I
Introduction to Differential Equations
Monetary theory & Policy
Financial Economics
Econometrics I
Numerical Analysis
Real Analysis II
Partial Differential Equations
Econometrics II
Pakistan Economic Policy
Topology
Complex Analysis
Economics Elective I
Mathematics Elective I
Time Series Analysis
Optimization Techniques
Functional Analysis
Economics Elective II
Mathematics Elective II
Project