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.

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 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.

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.

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.

Suggested Semester/Study Plan for BS DS

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

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.

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.

The duration to complete BS degree program is about 4 years. But HEC has allowed a maximum 6 year duration to complete their degrees.

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.

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
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

Funding

We offer several fully and partially funded undergraduate scholarships to full-time undergraduate students. Visit Funding Policy for further queries.

Department of Computer Science

Vision of the Department

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.

Mission of the Department

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.

 

Objectives of the Department

• 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 in
  Pakistan.
• Exercising commercialization through incubation of high tech companies. 

Degree Programs

Currently, the Department is offering the following undergraduate and postgraduate degree programs:

• Computer Science (BS)
• Software Engineering (BS)
• Data Science (BS)
• Computer Science (MS)
• Software Engineering (MS)

Related Degree Programs

• Mathematics (BS)
• Mathematics (MPhil)
• Physics (BS)
• Physics (MPhil)
• Civil Engineering Technology (BS)

Research Publications

2024

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.

Research Collaboration with International Universities

• Prince Sultan University, Riyadh, Saudi Arabia

• King Saud University, Riyadh, Saudi Arabia

• Taif University, Taif, Saudi Arabia

Research Collaboration with National Universities

• University of Kotli, Kotli, Azad Jammu & Kashmir
• IQRA University, Islamabad Campus, Islamabad
• RIPHAH University, Islamabad Campus, Islamabad
• COMSATS University, Sahiwal Campus, Sahiwal

People

Dr. Zeeshan Ashraf

Associate Professor/ Chairperson

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Dr. Babur Hayat Malik

Assistant Professor

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Umair Muneer Butt

Lecturer

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Dr. Sohaib Latif

Assistant Professor

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Imtiaz Ali Soomro

Lecturer

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Muhammad Saad Bin Ilyas

Lecturer

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Hafiza Maimoona Shahid

Lecturer

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Muhammad Aadil Butt

Lecturer

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Mehk Fatima

Lecturer

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Aneela Abbas

Lecturer

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Fizza Azhar

Lecturer

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Yasir Rashid Darr

Lecturer

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Raheel Baig

Lecturer

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Khalil Ul Rehman

Lecturer (On Study Leave)

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Syed Hammad Hussain

Lecturer

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Syeda Subhana Hashmi

Lecturer

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Industrial Linkage and MOUs

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

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