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Read the full noticeSchool of Computing
B.Sc. Computer Science
Programme Overview
The Computer Science programme at the University of Agriculture, Science and Technology, Ihugh (UAST) consists of a comprehensive undergraduate education in the scientific foundations of computation, algorithms, artificial intelligence, systems programming, high-performance computing, and computational innovation. For students in the programme, a core learning objective is building and demonstrating foundational competencies in computational thinking, algorithm design, scientific programming, parallel and distributed computing, artificial intelligence, and computational modelling through the successful completion of rigorous coursework, laboratory investigations, research projects, and a capstone scientific computing portfolio. Students are also eligible for accelerated research pathways, including postgraduate studies, industry research positions, and technology innovation ventures.
Programme Distinctiveness
A Curriculum Benchmark Internationally
The UAST Computer Science curriculum is benchmarked against leading computer science programmes at institutions including Massachusetts Institute of Technology, Stanford University, Carnegie Mellon University, ETH Zurich, and National University of Singapore, while addressing computational challenges and technology innovation priorities specific to Nigeria and Africa.
A Programme Rooted in National Priorities
While maintaining international standards, the programme equips graduates to address Nigeria's most pressing computing and technology challenges: artificial intelligence for development, computational agriculture, environmental informatics, cybersecurity, digital infrastructure, high-performance computing for scientific discovery, and technology innovation for economic transformation.
Integrated with National Academic Standards
The programme is structured around the National Universities Commission (NUC) Core Curriculum and Minimum Academic Standards (CCMAS), with a distinctive 30% UAST proprietary component that substantially strengthens competencies in computational thinking and scientific programming, advanced algorithms, parallel and concurrent computing, high-performance computing, cloud and distributed systems, artificial intelligence and intelligent systems, computer vision and robotics, quantum computing, computational science for agriculture and environmental systems, enterprise computing architecture, and research methodology.
The UAST Advantage: Professional Competencies
Graduates of this programme acquire competencies in:
- Computational Thinking and Scientific Programming
- Advanced Algorithms and Algorithm Engineering
- Systems Programming and Linux Administration
- Parallel and Concurrent Computing
- High-Performance Computing
- Cloud Computing and Distributed Systems
- Artificial Intelligence and Intelligent Systems
- Computer Vision and Intelligent Robotics
- Computational Modelling and Simulation
- Quantum Computing and Future Paradigms
- Computational Science for Agriculture and Environmental Systems
- Enterprise Computing Architecture and Digital Transformation
- Research Methods and Scientific Communication
Programme Structure
The programme is delivered over four academic years (100–400 Levels) and comprises UAST proprietary courses complementing the NUC 70% core curriculum.
Year One: Foundations
- Computational Thinking and Scientific Programming
- Digital Systems and Computer Organization Laboratory
- Technical Communication for Computing Professionals
- Emerging Frontiers in Computer Science
Year Two: Core Computational Competencies
- Advanced Algorithms and Computational Problem Solving
- Systems Programming and Linux Administration
- Parallel and Concurrent Computing
- Computational Modelling and Simulation
- Research Methods in Computer Science
Year Three: Advanced Computing and Intelligent Systems
- Artificial Intelligence and Intelligent Systems
- Cloud Computing and Distributed Systems
- High-Performance Computing
- Computer Vision and Intelligent Robotics
- Computational Science for Agriculture and Environmental Systems
Year Four: Research and Professional Integration
- Quantum Computing and Future Computing Paradigms
- Advanced Artificial Intelligence and Generative Systems
- Computing Innovation, Entrepreneurship and Technology Policy
- Enterprise Computing Architecture and Digital Transformation
- Research Project, Scientific Computing Portfolio and Capstone
Career Pathways
UAST Computer Science graduates are prepared for careers in:
Research and Academic Institutions
Computational science research, algorithm development, and postgraduate studies
Artificial Intelligence and Machine Learning
AI research, intelligent systems development, and data science
High-Performance Computing
Scientific computing, supercomputing applications, and computational engineering
Cloud and Distributed Systems
Cloud architecture, distributed applications, and scalable infrastructure
Systems and Infrastructure
Systems programming, Linux administration, and enterprise computing
Robotics and Automation
Intelligent robotics, autonomous systems, and computer vision
FinTech and Financial Computing
Algorithmic trading, risk modelling, and financial systems
Agriculture and Environmental Technology
Precision agriculture, environmental informatics, and computational sustainability
Technology Innovation and Entrepreneurship
Startup development, technology commercialization, and digital transformation
Cybersecurity and Digital Trust
Secure systems, cryptography, and digital forensics
Fast-Track and Professional Pathways
Qualified students are eligible for accelerated pathways, including:
Undergraduate Research
- Supervised research projects in collaboration with faculty and research institutions
Industrial Training (SIWES)
- Internships in technology companies, research laboratories, and government agencies
Innovation and Entrepreneurship
- Access to technology incubators and startup support
Postgraduate Pathways
- Progression to M.Sc. and Ph.D. programmes in Computer Science, Artificial Intelligence, Data Science, and related disciplines