Program Overview
The BS-DS&BA is designed for students seeking to bridge the gap between business and technology. In today’s data-driven world, organizations increasingly depend on professionals who can interpret complex data, identify trends, and make informed business decisions. This program provides a solid foundation in business, computation, and technology, emphasizing real-world applications of data analysis, artificial intelligence, and machine learning in business contexts. With companies leveraging data to gain a competitive advantage, graduates of this program will be highly sought after in both corporate and entrepreneurial environments.
The program incorporates the S&P Capital IQ Pro platform, giving students access to comprehensive real-time business and financial data, advanced analytics tools, and industry insights. Completion of the BS-DS&BA requires 146 credit hours over eight regular semesters (four years), including a mandatory internship (3 credit hours) and a Capstone project (3 credit hours). This structure allows students to gain hands-on experience in industries where data-driven decision-making is critical.
Graduates will be equipped to pursue careers in sectors such as banking, retail, healthcare, e- commerce, manufacturing, consulting, HR, and supply chain management. They will acquire the skills necessary to develop and implement data-driven business strategies in corporate settings. To graduate, students must maintain a CGPA of 2.5.
The curriculum includes 12 General Education courses (33 credit hours) completed during the first four semesters. Courses are organized into General Education, Interdisciplinary, Discipline-related, and Elective categories. Students can take a full load of six courses per Fall and Spring semester, with the option to enroll in remedial courses during the summer semester to address failures, improvements, or prerequisite requirements.
Mission
The mission of the BS Data Sciences and Business Analytics program is to develop analytically strong, ethically responsible, and industry-ready graduates who can transform data into actionable insights. Through a balanced curriculum integrating mathematics, statistics, computer science, business foundations, and advanced analytical techniques, the program aims to equip students with the skills necessary to solve real-world problems, support data-driven decision-making, and drive organizational innovation. We strive to foster critical thinking, creativity, and lifelong learning to prepare students for dynamic careers in data science, business analytics, and emerging digital domains.
Program Educational Objectives (PEOs)
Graduates of the BS Data Sciences & Business Analytics program are expected to achieve the following:
Program Learning Outcomes (PLOs)
Upon successful completion of the BS-DS&BA program, graduates will be able to:
Knowledge (Cognitive -Understanding)
Problem Analysis (Cognitive -Analyzing)
Data-Driven Solution Design (Cognitive -Creating)
Modern Tool Usage (Cognitive/Psychomotor -Applying)
Ethics and Data Governance (Affective -Valuing)
Communication (Affective/Cognitive - Applying)
Teamwork and Collaboration (Affective - Responding/Valuing)
Scheme Of Study
Scheme Of Study
Semester-wise Course Plan
Semester 1
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
SSC 101 |
Introduction to Psychology |
3 |
Nil |
|
2 |
ECO 101 |
Principles of Microeconomics |
3 |
Nil |
|
3 |
MTH 108 |
Business Mathematics and Statistics |
3 |
Nil |
|
4 |
MGT 101 |
Principles of Management |
3 |
Nil |
|
5 |
COM 107 |
Academic English |
3 |
Nil |
|
6 |
ACT 101 |
Introduction to Financial Accounting |
3 |
Nil |
|
Total Credit Hours Semester 1 |
18 |
|||
Semester 2
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
PSC 101 |
Pakistan studies |
3 |
Nil |
|
2 |
BCN 201 |
Persuasive Writing for Business Communication |
3 |
BCN 101 |
|
3 |
MAT 105 |
Linear Algebra and Calculus |
3 |
MAT 102 |
|
4 |
EEM 101 |
Environmental Studies |
3 |
Nil |
|
5 |
STS 202 |
Inferential Statistics |
3 |
MAT 102 |
|
6 |
MGT 102 |
Introduction to Management and Organizational Behavior |
3 |
Nil |
|
Total Credit Hours Semester 2 |
18 |
|||
Semester 3
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
LAN 30 |
Foreign language |
3 |
Nil |
|
2 |
PSC 201 |
Ideology and Constitution of Pakistan |
2 |
PSC 101 |
|
3 |
MRK 101 |
Fundamentals of Marketing Management |
3 |
ACT 101 |
|
4 |
FNS 201 |
Introduction to Business Finance |
3 |
ACS 101 |
|
5 |
BIA 101 |
Introduction to Business Analytics |
3 |
STS 202 |
|
6 |
BIA 102 |
Fundamentals of Programming |
3 |
MAT 105 |
|
Total Credit Hours Semester 3 |
17 |
|||
Semester 4
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
CSC 210 |
Applications of Information Communications Technologies |
3 |
Nil |
|
2 |
SSC 303 |
Civic Responsibility and Service-Learning |
3 |
Nil |
|
3 |
ETP 101 |
Entrepreneurship |
3 |
Nil |
|
4 |
BIA 201 |
SQL for Business Intelligence |
3 |
BIA 102 |
|
5 |
HRM 201 |
Human Resource Management |
3 |
MGT 102 |
|
6 |
ACS 301 |
Cost and Management Accounting |
3 |
ACS 101 |
|
Total Credit Hours Semester 4 |
18 |
|||
Semester 5
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
MGT 402 |
Leadership and Business Ethics |
3 |
MGT 102 |
|
2 |
BIA 202 |
Statistical modelling and Data Analytics |
3 |
STS 202,
BIA 101 |
|
3 |
BIA 203 |
Business Intelligence & Data Visualization |
3 |
BIA 201 |
|
4 |
BIA 204 |
Programming Applications for Business Analytics |
3 |
BIA 102 |
|
5 |
FNS 202 |
Financial Management |
3 |
FNS 201 |
|
6 |
BIA 302 |
HR Analytics for Business |
3 |
HRM 201 |
|
Total Credit Hours Semester 5 |
18 |
|||
Semester 6
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
BIA 303 |
Supply Chain and Operations Analytics |
3 |
Nil |
|
2 |
BIA 304 |
Big Data for Business Intelligence |
3 |
BIA 201, BIA 203 |
|
3 |
BIA 305 |
Business Research and Decision Analytics |
3 |
BIA 202 |
|
4 |
BIA 306 |
Machine Learning for Business |
3 |
BIA 202, BIA 204 |
|
5 |
MGT 403 |
Strategic Management |
3 |
MGT 402 |
|
6 |
BIA 307 |
Strategic Marketing Analytics |
3 |
MRK 101 |
|
Total Credit Hours Semester 6 |
18 |
|||
Semester 7
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
XXX |
Elective 1 |
3 |
Nil |
|
2 |
XXX |
Elective 2 |
3 |
Nil |
|
3 |
BIA 401 |
Time Series and Forecasting Models |
3 |
BIA 202 |
|
4 |
BIA 402 |
Deep Learning and AI for Business |
3 |
BIA 306 |
|
5 |
MGT 401 |
Technology and Innovation Management |
3 |
Nil |
|
6 |
BIA 403 |
Analytics in Financial Decision Making |
3 |
FNS 202 |
|
Total Credit Hours Semester 7 |
18 |
|||
Semester 8
| Sr. No | Course Code | Course Title | Cr. Hrs | Pre- Requisite |
|---|---|---|---|---|
|
1 |
XXX |
Elective 3 |
3 |
Nil |
|
2 |
XXX |
Elective 4 |
3 |
Nil |
|
3 |
XXX |
Elective 5 |
3 |
Nil |
|
4 |
XXX |
Elective 6 |
3 |
Nil |
|
5 |
BIA 404 |
Digital Marketing and Social Media Analytics |
3 |
BIA 307 |
|
6 |
BIA 481 |
Capstone – Business Intelligence and Analytics |
3 |
Nil |
|
Total Credit Hours Semester 8 |
18 |
|||
| Category | No. of Courses | No. of Credit Hour | ||
|---|---|---|---|---|
|
GE |
11 |
28 |
||
|
Major |
19 |
57 |
||
|
Inter-Dis |
12 |
35 |
||
|
Internship |
1 |
3 |
||
|
Project |
1 |
3 |
||
|
Elec |
6 |
18 |
||
|
Total Credit Hours Semester |
144 |
|||
Specializations
Finance
Marketing
Entrepreneurship
International Business
Human Resource Management
Supply Chain Management
Business Development
Develop expertise in financial management, investment analysis, and risk management to pursue careers in banking, financial institutions, or corporate finance
Learn about market research, brand management, digital marketing, and consumer behavior to drive business growth and customer engagement.
Focus on talent acquisition, employee development, and organizational behavior to become a strategic HR professional.
Understand global market dynamics, trade policies, and cultural differences to succeed in multinational corporations or international trade
Develop skills to start and grow your own business, including idea generation, business planning, and funding strategies
Optimize logistics, procurement, and distribution to ensure efficient and effective supply chain operations.
Experiential Learning
Industrial Visits
At DITE, we are dedicated to cultivating future business leaders and analytical thinkers through meaningful real-world engagement that complements academic learning. Our BS Data Science & Business Analytics students regularly participate in industrial visits to leading corporations, data-driven enterprises, startups, and business innovation hubs.
These visits provide students with first-hand exposure to contemporary business operations, analytical processes, and strategic decision-making frameworks employed by industry leaders. Through observation and interaction, students gain practical insights into how data analytics informs business growth, market competitiveness, and organizational efficiency.
By engaging with professionals in diverse business environments, students enhance their understanding of data-driven management, performance analysis, and evidence-based strategy formulation. Such experiences enable them to bridge theoretical learning with real-world practice, preparing them to navigate and contribute effectively to today’s data-centric business landscape.
Swipe through to see highlights from our recent visits, where learning meets innovation.
Eligibility Criteria
Applicants must meet the following eligibility requirements to be considered for admission.
| Qualification | Grade Requirements | Mathematics Requirements | Additional Requirements |
|---|---|---|---|
|
Intermediate |
Minimum 50% marks
in Intermediate. |
Students who have not studied Mathematics at the Intermediate level must pass Mathematics deficiency courses (6 Credit Hours) within the first two semesters. |
Passing of DITE’s Admission Test, Panel Discussion, and Interview. |
|
A-Levels |
A-Levels (Minimum 3 A-Levels passes with grade C or above)
|
Must have GCSE Mathematics
(Grade A*-C / 9–5)
|
Passing of DITE’s Admission Test, Panel Discussion, and Interview.
|
Fee Structure
The fee structure of BS Data Science & Business Analytics for the Academic Year 2026–27 is as follows:
| Description | BS Data Science & Business Analytics |
|---|---|
|
Tuition Fee |
Rs. 380,000/- |
|
Library Fee |
10,000/- |
|
Lab Fee |
20,000/- |
|
Student Activity Fee |
10,000/- |
|
Total Fees |
420,000/- |
- The tuition fee is indicative and may increase by up to 10%
- If a refund is requested, 10% will be deducted, in addition to the refund policies mentioned in the offer letter.
ADMISSIONS OPEN
2026-2027
SHAPE YOUR FUTURE WITH US
FAQs
The BS Data Science & Business Analytics at DITE is a four-year undergraduate degree that combines data science and business strategy. The program trains students to analyze data, develop predictive models, and make evidence-based decisions using advanced analytical and AI tools.
Graduates can pursue careers such as Business Analyst, Data Analyst, Marketing Analyst, Financial Analyst, Data Consultant, or AI Project Manager in both corporate and entrepreneurial settings.
Yes. DITE’s Career Development Unit assists students with internships, resume preparation, interview training, and professional networking with industry partners.
Yes. Transfer applications from HEC-recognized institutions are evaluated on a case-by-case basis, depending on course equivalence and academic performance.
Yes. DITE offers a range of scholarships. Students can obtain full details and eligibility criteria from the Finance Office.
Get in Touch with DITE
Take the first step towards your academic and career goals. Our team is here to guide you through program selection, admissions, and campus opportunities.
