- Data Science (BS)
Duration
4 years full-time
Qualification
Bachelor of Science in Data Science
Credit Hours
130
Academic Session
Spring and Fall
Program Overview
Program Objectives
Program Education Objectives (PEOs)
Program Learning Outcomes (PLOs)
Mapping of PLOs to PEOs
Mapping of CLOs to PLOs:
Courses Distribution
Specialization Areas
Teaching
Assessment Tools
Duration
Entry Requirement
Careers
Tuition Fee
Departments
Life at Chenab
Next Steps
Fall 2024 Entry
Program Overview
The Bachelor of Science in Data Science is an undergraduate degree program designed to prepare students with the necessary skills and knowledge to become data scientists. 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. The program focuses on developing analytical and computational skills required to analyze complex data sets, build predictive models, and make data-driven decisions. The program is designed to provide students with a solid foundation in mathematics, statistics, computer science, and domain-specific knowledge.
The field of data science has gained immense popularity in recent years due to the explosion of data generated by the digital age. Companies and organizations are increasingly relying on data science to gain a competitive edge and make informed business decisions. Data science is a highly interdisciplinary field that offers a range of career opportunities in areas such as healthcare, finance, marketing, and technology. The BS (Data Science) program is designed to equip students with the necessary skills to analyze complex data sets using statistical and machine learning models. The program includes courses in probability, statistics, data mining, database systems, programming, and visualization. The program also includes hands-on projects and internships that provide students with practical experience in applying their knowledge to real-world problems.
This program will prepare graduates for a career in data analysis, combining foundational statistical concepts with computational principles from computer science. Graduates of the program are well-equipped to work in a variety of industries, including healthcare, finance, marketing, and technology.
Program Objectives
Objectives of the DS Program:
- To develop students’ skills in programming languages, data processing, data analysis, and data visualization.
- To equip students with the ability to solve complex problems using data-driven approaches and machine learning techniques.
- To prepare students for careers in data science, data analysis, business analytics, and related fields.
- To provide students with opportunities to work on real-world data science projects and gain practical experience.
- To foster students’ critical thinking, problem-solving, and communication skills, which are essential for success in the data science field.
- To provide students with access to state-of-the-art facilities and resources, such as high-performance computing clusters, data analytics software, and data visualization tools
Program Education Objectives (PEOs)
Program Education Objectives of BS Data Science:
PEO 1 Computing knowledge, skills, and creativity: Apply computing knowledge and skills to design and develop effective solutions for complex real-life problems.
PEO 2 Ethics and social responsibility: Demonstrate ethical and moral conduct in professional practices.
PEO 3 Communication and Leadership Skills: Manifest life-long learning and inter-personal skills for sustainable career development and professional growth.
Program Learning Outcomes (PLOs)
Graduate Attributes (GAs) defined by National Computing Education Accreditation Council (NCEAC) are in alignment with the Graduate Attributes laid down in the Seoul Accord document D.5 for computing professionals.
According to the revised curriculum for computing disciplines by NCEAC with reference number 5-4/HEC/CURR/COMP/2023/4394, following are the PLOs for BSCS, BSSE, and BSDS.
Program Learning Outcomes (PLOs):
PLO1 Academic Education: To prepare graduates as computing professionals.
PLO2 Knowledge for Solving Computing Problems: Apply knowledge of computing fundamentals, knowledge of a computing specialization, and mathematics, science, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements.
PLO3 Problem Analysis: Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.
PLO4 Design/ Development of Solutions: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
PLO5 Modern Tool Usage: Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.
PLO6 Individual and Teamwork: Function effectively as an individual and as a member or leader in diverse teams and in multi-disciplinary settings.
PLO7 Communication: Communicate effectively with the computing community and with society at large about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.
PLO8 Computing Professionalism and Society: Understand and assess societal, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice.
PLO9 Ethics: Understand and commit to professional ethics, responsibilities, and norms of professional computing practice.
PLO10 Life-long Learning: Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.
Mapping of PLOs to PEOs
| No. | Program Learning Outcomes | PEOs | ||
|---|---|---|---|---|
| PEO 1 | PEO 2 | PEO 3 | ||
| 1 | Academic Education | |||
| 2 | Knowledge for Solving Computing Problems | |||
| 3 | Problem Analysis | |||
| 4 | Design/ Development of Solutions | |||
| 5 | Modern Tool Usage | |||
| 6 | Indivoval and leamwork | |||
| 7 | Communication | |||
| 8 | Computing Professionalism and Society | |||
| 9 | Ethics | |||
| 10 | Life-long Learning | |||
Mapping of CLOs to PLOs:
According to the revised curriculum for computing disciplines such as BSCS, BSSE, and BSDS by NCEAC with reference number 5-4/HEC/CURR/COMP/2023/4394, CLOs of every course have been mapped to its corresponding PLOs with Bloom Taxonomy (BT) levels.
Courses Distribution
Suggested Semester/Study Plan for BS DS
Semester – 1 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-1113 | Programming Fundamentals | – | 3 |
CSC-1111 | Programming Fundamentals – LAB | – | 1 |
CSC-1012 | Application of Information & Communication Technologies | – | 2 |
CSC-1011 | Application of Information & Communication Technologies – LAB | – | 1 |
ENG-1213 | Functional English | – | 3 |
MTH-1423 | Calculus and Analytical Geometry | – | 3 |
MTH-1413 | Discrete Structures | – | 3 |
Total | 16 | ||
Semester – 2 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-1123 | Object Oriented Programming | CSC-1113 | 3 |
CSC-1121 | Object Oriented Programming – LAB | CSC-1111 | 1 |
CSC-1022 | Digital Logic Design | – | 2 |
CSC-1021 | Digital Logic Design – LAB | – | 1 |
CSC-1033 | Database Systems | – | 3 |
CSC-1031 | Database Systems – LAB | – | 1 |
CSC-1042 | Computer Networks | – | 2 |
CSC-1041 | Computer Networks – LAB | – | 1 |
MTH-1433 | Linear Algebra | MTH-1423 | 3 |
Total | 17 | ||
Semester – 3 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-2133 | Data Structures & Algorithms | CSC-1123 | 3 |
CSC-2131 | Data Structures & Algorithms – LAB | CSC-1121 | 1 |
CSC-2063 | Software Engineering | – | 3 |
CSC-2082 | Artificial Intelligence | – | 2 |
CSC-2081 | Artificial Intelligence – LAB | – | 1 |
CSC-2072 | Information Security | – | 2 |
CSC-2071 | Information Security – LAB | – | 1 |
MTH-2443 | Probability & Statistics | – | 3 |
MTH-2453 | Multivariable Calculus | MTH-1423 | 3 |
Total | 19 | ||
Semester – 4 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-2142 | Computer Org. & Assembly Language | CSC-1022 | 2 |
CSC-2141 | Computer Org. & Assembly Language – LAB | CSC-1121 | 1 |
DSC-2512 | DC1 / Introduction to Data Science | CSC-2082 | 2 |
DSC-2511 | DC1 / Introduction to Data Science – LAB | CSC-2081 | 1 |
DSC-2522 | DC2 / Advanced Statistics | MTH-2443 | 3 |
PHY-2462 | Applied Physics | – | 2 |
PHY-2461 | Applied Physics – LAB | – | 1 |
ENG-2223 | Expository Writing | ENG-1213 | 3 |
CSE-2612 | Domain Elective I / Machine Learning | – | 2 |
CSE-2611 | Domain Elective I / Machine Learning – LAB | – | 1 |
Total | 18 | ||
Semester – 5 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-3052 | Operating Systems | – | 2 |
CSC-3051 | Operating Systems – LAB | – | 1 |
DSC-3532 | DC3 / Data Mining | DSC-2522 | 2 |
DSC-3531 | DC3 / Data Mining – LAB | DSC-2511 | 1 |
DSC-3542 | DC4 / Data Warehousing & Business Intelligence | DSC-2512 | 2 |
DSC-3541 | DC4 / Data Warehousing & Business Intelligence – LAB | DSC-2511 | 1 |
CSE-3622 | Domain Elective 2 / Big Data Analytics | DSC-2512 | 2 |
CSE-3621 | Domain Elective 2 / Big Data Analytics – LAB | DSC-2511 | 1 |
CSE-3632 | Domain Elective 3 / Advanced Database Management Systems | – | 2 |
CSE-3631 | Domain Elective 3 / Advanced Database Management Systems – LAB | – | 1 |
MGT-3312 | Social Science / Introduction to Management | – | 2 |
Total | 17 | ||
Semester – 6 | |||
Code | Course Title | Pre-req | Credit Hrs |
DSC-3552 | DC5 / Data Visualization | DSC-3542 | 2 |
DSC-3551 | DC5 / Data Visualization – LAB | DSC-3541 | 1 |
DSC-3562 | DC6 / Parallel & Distributed Computing | – | 2 |
DSC-3561 | DC6 / Parallel & Distributed Computing – LAB | – | 1 |
CSE-3642 | Domain Elective 4 / Text Mining | – | 2 |
CSE-3641 | Domain Elective 4 / Text Mining – LAB | – | 1 |
CSE-3652 | Domain Elective 5 / Theory of Automata | – | 2 |
CSE-3651 | Domain Elective 5 / Theory of Automata – LAB | – | 1 |
CSE-3662 | Domain Elective 6 / HCI & Computer Graphics | – | 2 |
CSE-3661 | Domain Elective 6 / HCI & Computer Graphics – LAB | – | 1 |
CSE-3672 | Domain Elective 7 / Artificial Neural Networks & Deep Learning | – | 2 |
CSE-3671 | Domain Elective 7 / Artificial Neural Networks & Deep Learning – LAB | – | 1 |
Total | 18 | ||
Semester – 7 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-4712 | Final Year Project – I | – | 2 |
CSC-4093 | Analysis of Algorithms | CSC-2133 | 3 |
MGT-4383 | Elective Supporting Course / Introduction to Marketing | – | 3 |
ENG-4233 | Technical and Business Writing | ENG-1213 | 3 |
HUM-4342 | Islamic Studies/ Ethics | – | 2 |
HUM-4322 | Entrepreneurship |
| 2 |
Total | 15 | ||
Semester – 8 | |||
Code | Course Title | Pre-req | Credit Hrs |
CSC-4724 | Final Year Project – II | CSC-4712 | 4 |
HUM-4352 | Professional Practices | – | 2 |
HUM-4372 | Ideology and Constitution of Pakistan | – | 2 |
HUM-4362 | Civics and Community Engagement | – | 2 |
Total | 10 | ||
Specialization Areas
This program has vast canvas of following specialization areas.
- Data Science
- Machine Learning
- Artificial Intelligence
- Cyber Security
- Computer Networking
- Mobile Application Development
- Web Application Development
Teaching
In BSDS we use various methods of teachings through classroom activities including a combination of lectures, tutorials, lab sessions, seminars, workshops, online learning, and independent study. In addition to these workshops, online learning and seminars are also considered. Mode of communication is English.
This program structure is comprised of a total number of thirty to thirty-two lectures and about 3 hours per week will be allocated for teaching and sixteen labs. Each lab consists of three hours of lab practice per week. You will be guided al about the studies, mainly about time for preparing classes, completion of research projects, and reading of primary texts. This program is taught in an appropriately positive learning environment for quality composing work to take place.
Our Data Science (BSDS) degree is undertaken in a better, more open, and more connected environment to keep more students engaged in a classroom.
Assessment Tools
Mainly evaluation will be concluded by extensive monitoring of written examination and course work completion along with routine quizzes, individual assignments, and group tasks i.e. programming such as writing, research and presentation.
Duration
The duration to complete BS degree program is about 4 years. But HEC has allowed a maximum 6 year duration to complete their degrees.
Entry Requirement
Before applying for a degree, you should first check that we recognize your higher secondary/tertiary education qualification. This can include:
- Pakistani Based Examinations: Higher Secondary School Certificate (HSSC) or equivalent with Mathematics or three years Diploma of Associate Engineer (DAE) in any discipline
- British System: GCE A Level with any of following subjects Further Mathematics/Pure Mathematics/Mathematics.
- International Baccalaureate (IB): The International Baccalaureate Diploma Program (DP) from external Examining body Geneva, Switzerland with five subjects (including Mathematics)
- You still can be admitted if you have passed additional deficiency courses prescribed by the relevant faculty.
- Candidates without mathematics can be admitted provided that they must have to pass deficiency courses of Mathematics of 6 credit hours in first two semesters.
- Equivalence Certificate for A-Level/IB and other qualification holders from Inter Board Committee of Chairman (IBCC) Islamabad, Pakistan.
- Admission test administered by the university.
- 50% marks are required in all cases described above.
Careers
Students from the Department of Computer Science can start their careers in the any of following industries and companies:
Automobiles and Aviation Toyota, Suzuki, Honda, Cavalier
Computer Systems NetSol, TechAbout, KalSoft, Techlogix
Computer Security TISS, Tier3, PakCERT, Catalytic Security
Consumer goods Nishat, Ashabi, Stallion Textile Mills
Finance SBP, NBP, HBL, MCB
Software Beltok, Nets Tech, Webicosoft, Glowlogix
Research Higher Education Institutions
Bachelor of Data Science degree holders are eligible for pursuing their Postgraduate degrees in the subject of Computer Science and its related areas and thus become further capable for the job of Data Science researcher, Web Developer, Software Engineer, System Analyst, University academic, Economist, Statistician, and many others.
They can pursue roles such as:
- Software engineer
- Systems analyst
- Investment analyst
- Web designer/developer
- Business analyst
- Actuary
- Economist and statistician
- Computer science researcher
- University academic
- Teacher
- Entrepreneur
- Start-up owner
Helping you find the right career
We have the facilities of devoted career counselors who help you to select your career choices and assist you in preparing for various recruitment programs. You can also be a part of career fest programs which are an interactive session with the recruiters so, you can understand their requirements and recruitment criteria.
Tuition Fee
Tuition Fee
Mainly tuition fees majorly covers our study cost, which includes assessment and teaching. Advanced fees are taken before the academic semester. If the university takes fees directly then you can choose the installment methods to pay your fees.
Additional course costs
You may be charged an extra cost of additional things such as books, stationery, recreational and study trips, and other materials.
Fee Structure Fall 2024
| Semester | Courses | CrdHrs | Tuition Fee/CrdHr | Tuition Fee/Semester | Enrollment Fee (500 per Course) | Examination Fee (500 per Course) | Medical Diagnostic Charges (500 per Semester) | Societies & Club Fee (2500 per Semester) | Total Fee For Semester |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 7 | 16 | 6,200 | 99,200 | 3,500 | 3,500 | 500 | 2,500 | 109,200 |
| 2 | 9 | 17 | 6,200 | 105,400 | 4,500 | 4,500 | 500 | 2,500 | 117,400 |
| 3 | 9 | 19 | 6,500 | 123,500 | 4,500 | 4,500 | 500 | 2,500 | 135,500 |
| 4 | 11 | 18 | 6,500 | 117,000 | 5,500 | 5,500 | 500 | 2,500 | 131,000 |
| 5 | 11 | 17 | 6,800 | 115,600 | 5,500 | 5,500 | 500 | 2,500 | 129,600 |
| 6 | 12 | 18 | 6,800 | 122,400 | 6,000 | 6,000 | 500 | 2,500 | 137,400 |
| 7 | 6 | 15 | 7,100 | 106,500 | 3,000 | 3,000 | 500 | 2,500 | 115,500 |
| 8 | 4 | 10 | 7,100 | 71,000 | 2,000 | 2,000 | 500 | 2,500 | 78,000 |
| Total | 69 | 130 | 860,600 | Total Semesters Fee | 953,600 | ||||
| Registration Fee (payable once – Non Refundable) | 20,000 | ||||||||
| Total Fee | 973,600 | ||||||||
Funding
We offer several fully and partially funded undergraduate scholarships to full-time undergraduate students. Visit Funding Policy for further queries.
Departments
To be an international partner in computing education, research and development with our graduates impacting the society as computing professionals and entrepreneurs demonstrating professional integrity and leadership.
Department works with a clear mission to provide the country with trained resources for development of high-tech products and services and to exercise commercialization through incubation of high-tech companies.
- To produce best quality Computer Science & IT professionals and researchers by providing state-of-the-art training, hands on experience, and healthy research environment.
- To collaborate with industry and academia around the globe for achieving quality technical education and excellence in research through active participation of all the stakeholders.
- To promote academic growth by establishing Center of Excellences and offering inter-disciplinary postgraduate and doctoral programs.
- To establish and maintain an effective operational environment and deliver quality, prompt, cost effective and reliable technology services to the society as well as compliment the local and global economic goals.
- Making world class technology available to undertake large and complex IT Projects inPakistan.
- Exercising commercialization through incubation of high tech companies.
Currently, the Department is offering the following undergraduate and postgraduate degree programs:
2024
Ejaz, S., Baig, R., Ashraf, Z., Alnfiai, M. M., Alnahari, M. M., & Alotaibi, R. M. (2024). A deep learning framework for the early detection of multi-retinal diseases. PLOS ONE, 19(7), e0307317.
Shaukat, F., Ejaz, N., Ashraf, Z., Alnfiai, M. M., Alnahari, M. M., & Alotaibi, R. M. (2024). GenVis: Visualizing Genre Detection in Movie Trailers for Enhanced Understanding. IEEE Access.
Ashraf, Z., Sohail, A., & Iqbal, M. (2024). Design and Implementation of Lightweight Certificateless Secure Communication Scheme on Industrial NFV-Based IPv6 Virtual Networks. Electronics, 13(13), 2649.
Mahmood, Z., Ashraf, Z., Iqbal, M., & Farooq, B. (2024). User-trust centric lightweight access control for smart IoT crowd sensing applications in healthcare systems. Personal and Ubiquitous Computing, 28(2), pp. 1-14.
2023
Ashraf, Z., Sohail, A., Hameed, A., Farhan, M., Alotaibi, F. A., & Alnfiai, M. M. (2023). Robust and Lightweight Remote User Authentication Mechanism for Next-Generation IoT-based Smart Home. IEEE Access 11, pp. 137899 – 137910
Ashraf, Z., Mahmood, Z., & Iqbal, M. (2023). Lightweight Privacy-Preserving Remote User Authentication and Key Agreement Protocol for Next-Generation IoT-Based Smart Healthcare. Future Internet, 15(12), 386.
Ashraf, Z., Sohail, A., & Yousaf, M. (2023). Lightweight and authentic symmetric session key cryptosystem for client–server mobile communication. The Journal of Supercomputing, 1-25.
Ashraf, Z., Sohail, A., & Yousaf, M. (2023). Robust and lightweight symmetric key exchange algorithm for next-generation IoE. Internet of Things, 22, 100703.
Ashraf, Z., Sohail, A., Latif, S. A., Pitafi, A. H., & Malik, M. Y. (2023). Challenges and Mitigation Strategies for Transition from IPv4 Network to Virtualized Next-Generation IPv6 Network. Int. Arab J. Inf. Technol., 20(1), 78-91.
Butt, U. M., Arif, R., Letchmunan, S., Malik, B. H., & Butt, M. A. (2023). Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI. Computers, Materials & Continua, 76(2).
Ikram, A., Butt, M. A., & Tariq, I. (2023). Comparative Analysis of Regression Algorithms used to Predict the Sales of Big Marts. Journal of Innovative Computing and Emerging Technologies, 3(1).
Butt, M. A., Danjuma, S., Ilyas, M. S. B., Butt, U. M., Shahid, M., & Tariq, I. (2023). Demand Prediction on Bike Sharing Data Using Regression Analysis Approach. Journal of Innovative Computing and Emerging Technologies, 3(1).
2022
Butt, U. M., Ullah, H. A., Letchmunan, S., Tariq, I., Hassan, F. H., & Koh, T. W. (2023). Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences. Computers, Materials & Continua, 74(3).
Butt, U. M., Letchmunan, S., Hassan, F. H., & Koh, T. W. (2022). Hybrid of deep learning and exponential smoothing for enhancing crime forecasting accuracy. Plos one, 17(9), e0274172.
Baig, R., Rehman, A., Almuhaimeed, A., Alzahrani, A., & Rauf, H. T. (2022). Detecting malignant leukemia cells using microscopic blood smear images: a deep learning approach. Applied Sciences, 12(13), 6317.
Fatima, M., Rextin, A., Nasim, M., & Yusuf, O. (2022, October). Digital Information Seeking and Sharing Behaviour During the COVID-19 Pandemic in Pakistan. In Multidisciplinary International Symposium on Disinformation in Open Online Media (pp. 44-62). Cham: Springer International Publishing.
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- University of Kotli, Kotli, Azad Jammu & Kashmir
- IQRA University, Islamabad Campus, Islamabad
- RIPHAH University, Islamabad Campus, Islamabad
- COMSATS University, Sahiwal Campus, Sahiwal
Department of computer science has built strong linkage with industry and signed various MOUs with different software houses for jobs and internships.
Recently the University of Chenab has signed MOUs with following software houses.
- KMS Enterprise Solutions in Canada
- Techno Verse
- Twin Spider
- Dev Valley
- Cipher Coders
- Soft Pin
- Huawei ICT Academy
- Gujrat Chamber of Commerce and Industries
Led By
Life at Chenab
Peaceful ambience, agile teaching as well as non-teaching staff, and a disciplined yet enjoyable and motivating atmosphere. Welcome to the University of Chenab. We produce professionals who are adept in their disciplines. Our institution is not only concerned with grades and education, but also take care of mental well-being of our students.
The University of Chenab
Our Mission
The University of Chenab represents excellence in teaching, research, scholarship, creativity and engagement. Its mission is to produce professionals outfitted with the highest standards in creativity, transfer and application of knowledge dissemination to address issues of our time.
The UChenab sculpts its graduates to become future leaders in their fields to inspire the next generation and to advance ideas that benefit the world.
The University of Chenab
Our Vision
The University of Chenab, Gujrat aspires to become a nationally and internationally recognized university that distinguishes itself as an embedding center for outstanding ethical and moral values, teaching quality, learning outcomes, and richness of the student experience.
The University of Chenab, Gujrat envisions a transformative impact on society through its continual innovation in education, creativity, research, and entrepreneurship.
Next Steps
Finding Your
Course
- Visit (Website link admission tab) and search your respective course and department on this website.
- Check the admission criteria and learn about the eligibility criteria of your selected course.
- If you are confused about the fee structure visit our fee guide at (link)
- To search more about the campus and studies visit other events and tabs to learn about the latest news and events.
- Still if there are any ambiguities then contact our admission office.
Apply Online
- Search the page and select your course scroll to the menu and click on and option ‘Apply.’
- Fill the online application form with the required attachments.
- After the form is submitted then you’ll receive a confirmation email. Confirm your application which is then processed forward.
In-Campus Test
- After the acceptance of the online registration a date and time is allocated for an in-campus test.
- You must bring your original attested documents on your test day.
Results And Enrolment
- After sometimes the results are out so constantly check your email for the notification.
- Visit the campus for enrolment.
Final Steps
- After the enrolment attend your orientation day as it is an interactive session among students and the faculty.
- Then, receive your timetable.
- Finally, start a new step of your carrier.
Fall 2024 Entry
