Ziauddin University

Ziauddin University, through its Faculty of Engineering Science & Technology (ZUFESTM), proudly offers the Master of Science (MS) in Computer Science programme. This advanced postgraduate degree is designed to address the dynamic needs of the global technology landscape by developing professionals with strong theoretical foundations, advanced technical capabilities, and a robust research orientation.

Students may choose from specialisations such as Artificial Intelligence, Data Science, Cybersecurity, Software Engineering, and Cloud Computing. The programme emphasises case-based learning, practical research experience, and industry-focused projects, all delivered under the guidance of experienced faculty and supported by state-of-the-art laboratory facilities.

The MS programme fosters innovation, ethical leadership, and entrepreneurial thinking, equipping graduates for impactful careers in academia, industry, and research—both nationally and internationally.  

Vision

To be a leading hub of innovation and excellence in computing—shaping future-ready professionals, pioneering research, and transformative solutions in the ever-evolving world of technology.

Mission

Our mission is to produce competent graduates with a strong grasp of the theoretical foundations of computer science and practical expertise in designing, analyzing, and implementing complex computing systems. We aim to bridge the gap between academic knowledge and real-world challenges by fostering problem-solving abilities and innovation. 

In addition to technical proficiency, we emphasize the development of effective verbal and written communication skills, ethical responsibility, and a commitment to lifelong learning—empowering our students to contribute meaningfully to individual growth, knowledge advancement, and the betterment of society.

Programme Educational Objectives (PEO)

PEO 1:
To produce graduates with strong theoretical and practical foundations in computer science, including programming, data structures, algorithms, operating systems, and software engineering.

PEO 2:
To produce graduates capable of designing, developing, and analyzing efficient computing solutions for real-world problems using emerging technologies and tools.

PEO 3:
To produce graduates who demonstrate ethical responsibility, effective communication skills, and the ability to work independently or as part of a team while exhibiting leadership and entrepreneurial potential.

PEO 4:
To produce graduates who recognize the value of lifelong learning through continuous professional development, industry certifications, and advanced academic or research pursuits.

Lab Facilities

Lecture Rooms & Instructional Facilities

  • Room Type: Dedicated and Shared Lecture Rooms
  • Lecture Room Size: Each room is approximately 350 square feet in size.
  • Available Space per Student: 30 square feet per student.
  • Instructional Equipment: Each lecture room is equipped with a whiteboard, multimedia projectors, speaker system, computers, and internet connectivity.
  • Additional Amenities: The rooms are fully air-conditioned for a comfortable learning environment.
Laboratories

Lab Name

Timings

Facilities

Lab Space per Student

Computing Lab

Weekdays (8:30am–4:30pm)

32 Workstations (Core i3/i5, 3rd & 6th Gen), High-end Software, LAN/Wi-Fi, Scanner, Printing, Whiteboard, Multimedia

40 sq. ft

Operating System Lab

Weekdays (8:30am–4:30pm)

5 Workstations (Core i3/i5, 3rd & 6th Gen), High-end Software, LAN/Wi-Fi, Printing Facility

40 sq. ft

Final Year Project Lab

Weekdays (8:30am–4:30pm)

3 Workstations (Core i3/i5, 3rd & 6th Gen), High-end Software, LAN/Wi-Fi, Printing, Sensors, Potentiometer, 22″ LCD with HDMI, Extension Board

Not specified

Why Choose BS Computer Science

Choosing BS Computer Science at Ziauddin University offers many benefits for students who want to build a successful career in technology. Here’s why you should consider it:

  1. Complete Learning Program: Our Computer Science program covers everything you need to know about the field, from coding and algorithms to artificial intelligence and data science. This ensures you’re prepared for various tech careers.
  2. Practical Experience: You’ll get to work in modern labs equipped with the latest tools and technology. This hands-on experience will help you learn by doing, so you’re ready for real-world challenges.
  3. Expert Faculty: Our professors are experienced in both teaching and working in the tech industry. They’ll guide you through your studies and share valuable insights that will help you succeed.
  4. Research and Innovation: If you’re interested in research, you’ll have the opportunity to explore new areas in technology like AI, machine learning, and cybersecurity. This helps you develop critical problem-solving skills.
  5. Industry Connections: Ziauddin University has strong links with top tech companies, offering you chances for internships, projects, and networking. This makes it easier for you to step into the tech world after graduation.
  6. Collaborative Environment: You’ll work in a supportive environment where creativity, teamwork, and innovation are encouraged. This helps you develop skills that are important for tech jobs.
  7. Global Opportunities: With a degree from Ziauddin University, you’ll be prepared to work anywhere in the world. We ensure our program meets global standards, so you can compete in the international job market.
  8. Commitment to Excellence: We focus on providing quality education and helping students gain both academic knowledge and practical skills. Our program is designed to set you up for success in the fast-changing world of technology.

Salient Features

Comprehensive core curriculum: The Computer Science program offers a well-structured curriculum covering essential areas such as programming, algorithms, data structures, software engineering, computer networks, operating systems, and artificial intelligence. The curriculum is aligned with current academic standards and evolving industry needs.

  • Strong programming foundation: Students gain hands-on experience in widely used programming languages such as C++, Java, and Python, enabling them to develop efficient software solutions and contribute to modern software ecosystems.
  • Emphasis on problem-solving and logic building: The program focuses on enhancing students’ analytical thinking, computational logic, and algorithmic skills, essential for solving real-world problems using innovative approaches.
  • Exposure to emerging technologies: Students are introduced to trending areas such as machine learning, cloud computing, cybersecurity, mobile and web application development, giving them a competitive edge in the tech industry.
  • Project-based learning and industry alignment: Through final year projects, internships, and industry collaborations, students apply theoretical knowledge to practical problems, preparing them for workplace challenges.
  • Communication and teamwork skills: The program also emphasizes the development of soft skills, such as effective communication, teamwork, and project management, enabling students to thrive in interdisciplinary environments.
Location & Infrastructure

Campus Location: North Campus (ZUFESTM), F-103, Block B, North Nazimabad, Karachi.

Covered Area: The ZUFESTM area spans 18,000 square feet (approximately 2,000 square yards), while the SE Department occupies 180 square feet.

Building Ownership: The facilities are located in a university-owned building.

Applicants seeking admission to the MS in Computer Science programme must fulfil the following requirements:

  • Hold a 16-year degree (BS or equivalent) in Computer Science, Information Technology, or a closely related discipline from an HEC-recognised institution.
  • Possess a minimum CGPA of 2.0 out of 4.0, or at least 60% marks in the qualifying degree.  
Duration and Semester-Wise Break-Up (Thesis or Coursework)

The MS in Computer Science programme is structured to be completed in a minimum of 1.5 years, with an allowable extension of up to 4 years. Students have the flexibility to pursue one of the following pathways:

  • Coursework Only: Ideal for those seeking a professional focus without a research component.
  • Coursework + Thesis: Designed for students aiming to deepen their research skills and pursue academic or research-oriented careers.

Both options are aligned with HEC guidelines and offer a well-balanced combination of core and elective courses, with the thesis pathway involving supervised research on a specialised topic within the field. 

Core courses
Course Code Course Title
CS 701 Research Methodology
CS 702 Advanced Operating Systems
List of Elective Courses
Course Code Course Title
CS 703 Operations Research
CS 704 Independent Research Study-1
CS 705 Advanced Analysis of Algorithms
CS 706 Advanced Computer Architecture
CS 707 Advanced Database Design
CS 708 Advanced Theory of Computation
CS 709 Theory of Programming Languages
CS 710  Independent Research Study-2
CS 711 Internet Programming
CS 712 Machine Learning
CS 713 Computer Vision
CS 714 Digital Image Processing
CS 715 Data Mining
CS 716 Deep Learning
CS 717 Advanced Resource Sharing Architecture
CS 718 Expert Systems
CS 719 Distributed Computing
CS 720 Digital Forensics
CS 721 Artificial Intelligence 
CS 722 Deep Learning 
CS 723 Advanced Big Data Analytics
CS 724 Natural Language Processing
TH Thesis
Duration and Semester-Wise Break-Up (Thesis or Course Work)

The MS in Computer Science program is structured to be completed in a minimum of 1.5 years, with an allowable extension of up to 4 years. Students have the flexibility to pursue one of the following pathways:

  • Coursework Only: Ideal for those seeking a professional focus without a research component.
  • Coursework + Thesis: Designed for students aiming to deepen their research skills and pursue academic or research-oriented careers.

Both options are aligned with HEC guidelines and offer a well-balanced combination of core and elective courses, with the thesis pathway involving supervised research on a specialised topic within the field.

Program Overview
Option Coursework Only Coursework + Thesis
Typical Duration 1.5 Years 1.5 Years 
Minimum Credit Hours 30 30
Courses Required 10 Courses (30 Credit Hours) 8 Courses (24 Credit Hours) + Thesis (6 Credit Hours)
Core Courses 4 4
Elective Courses 6 4
Thesis Credit Hours N/A 6
Thesis Guidelines

As per University Policy

Degree Requirements

As per University Policy

Computer Science is a dynamic and fast-evolving field, offering extensive career opportunities across technology, healthcare, finance, education, and government sectors. The MS in Computer Science programme prepares graduates with strong foundations in programming, problem-solving, and research, enabling them to take on both technical and leadership roles. Graduates are well-equipped to drive digital transformation through roles in software development, data analysis, cloud computing, AI, and more.

Graduates may pursue careers in the following areas:

  • Software Developer/Engineer: Skilled in languages like Python, Java, and C++, with expertise in software design, development, testing, and maintenance.
  • Front-end Developer: Proficient in HTML, CSS, JavaScript, and frameworks like React or Angular, focusing on user interface design and interactive web applications.
  • Back-end Developer: Experienced in server-side programming using Java, Python, or Ruby, managing databases, APIs, and application performance.

  • Full-stack Developer: Versatile in both front-end and back-end technologies, capable of handling end-to-end development using tools like MERN or MEAN stacks.
  • Mobile App Developer: Specialises in iOS and Android development using Swift, Kotlin, or Flutter to build responsive and intuitive mobile applications.
  • Game Developer: Uses engines like Unity or Unreal Engine with programming in C# or C++ to create immersive gaming experiences.
  • DevOps Engineer: Combines software development and IT operations, skilled in automation tools, CI/CD pipelines, cloud platforms, and containerisation.
  • Embedded Systems Engineer: Works with C/C++ to develop software for hardware devices in sectors like automotive, medical, and consumer electronics.
  • Cloud Engineer: Proficient in AWS, Azure, or Google Cloud, managing cloud infrastructure, deployment, and security.
  • Cybersecurity Specialist: Knowledgeable in network security, encryption, ethical hacking, and incident response to protect digital systems.
  • Data Scientist: Applies machine learning, statistics, and data visualisation tools like Python, R, and SQL to analyse complex datasets and drive insights.
  • Machine Learning Engineer: Designs and deploys machine learning models using Python, TensorFlow, or PyTorch to automate decision-making processes.
  • Business Intelligence Analyst: Uses tools like Power BI, Tableau, and SQL to analyse data and provide actionable business insights.
  • IT Consultant: Advises on IT strategies and system implementations, requiring both technical knowledge and business acumen.
  • Data Engineer: Builds and maintains scalable data pipelines and storage systems using technologies like Hadoop, Spark, and NoSQL databases.
  • Cloud Architect: Designs enterprise-level cloud solutions focusing on scalability, security, and cost-efficiency across cloud platforms.
  • Systems Administrator: Manages servers, networks, and infrastructure, ensuring system reliability and performing routine maintenance and troubleshooting.

Graduates are also encouraged to engage in research by:

  • Designing experiments or building innovative prototypes
  • Publishing in academic journals and conferences
  • Exploring emerging areas like ethical AI, quantum computing, and edge computing

The programme supports pathways to R&D roles, doctoral studies, and academic careers, combining technical expertise with a research-driven mindset. 

The Programme Learning Outcomes (PLOs) for the MS in Computer Science programme are aligned with national and international standards for computing education. These outcomes define the expected capabilities and competencies of graduates, ensuring they are prepared for successful careers in industry, academia, and research. 

Program Learning

Outcomes (PLOs)

Computing Professional Graduate Outcomes
1. Academic EducationPrepare graduates to function as competent and effective computing professionals with a strong academic foundation.
2. Knowledge for Solving Computing ProblemsApply knowledge of computing fundamentals, domain-specific knowledge, mathematics, and science to abstract, conceptualise, and solve computing problems based on defined requirements.
3. Problem AnalysisIdentify, formulate, and analyse complex computing problems using principles from computing, mathematics, and relevant disciplines, leading to well-substantiated conclusions.
4. Design/Development of SolutionsDesign, develop, and evaluate computing solutions for complex problems, ensuring that designs meet specified requirements while considering societal, environmental, cultural, and public health aspects.
5. Modern Tool UsageSelect, adapt, and utilise modern computing tools, technologies, and methodologies effectively for complex computing tasks, recognising their scope and limitations.
6. Individual and Team WorkWork effectively as an individual and as a team member or leader in diverse, multidisciplinary environments.
7. CommunicationCommunicate effectively with both the computing community and broader society through well-structured reports, technical documentation, presentations, and clear instructions.
8. Computing Professionalism and SocietyDemonstrate an understanding of the societal, legal, cultural, health, and safety implications of computing practices, and accept the responsibilities associated with professional computing roles in a global context.
9. EthicsUphold and commit to ethical principles, professional responsibilities, and the norms of computing practice.
10. Lifelong LearningRecognise the importance of, and possess the ability to engage in, continuous self-directed learning and professional development in the computing field.
Fee Description Collection Type Non Subject Fee # of Cr. Hr Fee/Cr. Hr Amount
Admission Fee One Time 15,000 15,000
Security Deposit One Time
Application Fee One Time 2,500 2,500
Tuition Fee Semester 10 5,000 50,000
Examination Fee Semester 10 500 5,000
Other Charges Semester
Semester Registration Fee Semester 5,000 5,000
Total Fees — — — — 77,500