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Read the full noticeSchool of Computing
B.Sc. Data Science
Programme Overview
The Data Science programme at the University of Agriculture, Science and Technology, Ihugh (UAST) consists of a comprehensive undergraduate education in the extraction of knowledge from large, complex, and heterogeneous datasets using statistical methods, artificial intelligence, machine learning, computational modelling, and domain-specific analytics to support evidence-based decision-making. For students in the programme, a core learning objective is building and demonstrating foundational competencies in data engineering, statistical computing, machine learning, deep learning, spatial analytics, cloud computing, and responsible artificial intelligence through the successful completion of rigorous coursework, laboratory investigations, and a capstone research project. Students are also eligible for accelerated professional pathways, including postgraduate research, industry leadership, and entrepreneurial ventures in the rapidly expanding data science sector.
Programme Distinctiveness
A Curriculum Benchmark Internationally
The UAST Data Science curriculum is benchmarked against leading data science programmes at institutions including Massachusetts Institute of Technology, Stanford University, Carnegie Mellon University, ETH Zurich, and National University of Singapore, while addressing data-driven challenges in agriculture, healthcare, environmental management, finance, and governance 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 data-driven challenges: precision agriculture and food security, climate analytics and environmental monitoring, health informatics and disease surveillance, financial technology and business intelligence, smart governance and digital transformation, and sustainable resource management.
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 Python programming for data science, applied statistical computing with R and Python, cloud computing and big data infrastructure, machine learning and predictive analytics, deep learning and intelligent systems, spatial data analytics and GIS, data science for agriculture and environmental systems, advanced artificial intelligence and decision intelligence, financial data analytics and FinTech, data governance and cyber resilience, and innovation and entrepreneurship.
The UAST Advantage: Professional Competencies
Graduates of this programme acquire competencies in:
- Data Science Foundations
- Python Programming for Data Science
- Database Systems and Data Engineering
- Applied Statistical Computing
- Cloud Computing and Big Data Infrastructure
- Data Visualization and Storytelling
- Machine Learning and Predictive Analytics
- Deep Learning and Intelligent Systems
- Data Mining and Knowledge Discovery
- Spatial Data Analytics and GIS
- Data Science for Agriculture and Environmental Systems
- Responsible Artificial Intelligence and Ethics
- Advanced Artificial Intelligence and Decision Intelligence
- Financial Data Analytics and Business Intelligence
- Data Governance and Cyber Resilience
- Data Science Innovation and Entrepreneurship
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
- Foundations of Data Science and Digital Society
- Python Programming for Data Science
- Digital Productivity Tools and Scientific Communication
- Computational Thinking and Algorithm Design
Year Two: Core Data Competencies
- Database Systems and Data Engineering
- Data Visualization and Storytelling
- Applied Statistical Computing with R and Python
- Cloud Computing and Big Data Infrastructure
- Ethics, Privacy and Responsible Artificial Intelligence
Year Three: Advanced Analytics and Applications
- Machine Learning and Predictive Analytics
- Deep Learning and Intelligent Systems
- Data Mining and Knowledge Discovery
- Spatial Data Analytics and GIS
- Data Science for Agriculture, Health and Environmental Systems
Year Four: Research and Professional Integration
- Advanced Artificial Intelligence and Decision Intelligence
- Financial Data Analytics, Business Intelligence and FinTech
- Data Governance, Cyber Resilience and Digital Trust
- Data Science Innovation, Entrepreneurship and Technology Consulting
- Research Project, Professional Portfolio and Capstone
Career Pathways
UAST Data Science graduates are prepared for careers in:
Data Science and Analytics
Data scientists, machine learning engineers, and analytics consultants
Agricultural Technology (AgriTech)
Precision agriculture analytics, crop modelling, and smart farming systems
Environmental Informatics
Environmental monitoring, climate analytics, and sustainability data science
Health Informatics and Public Health
Disease surveillance, epidemiological modelling, and healthcare analytics
Financial Technology (FinTech)
Fraud detection, credit scoring, algorithmic trading, and customer analytics
Business Intelligence and Enterprise Analytics
Performance dashboards, predictive analytics, and strategic decision support
Government and Public Administration
Smart governance, policy analytics, and digital transformation
Research and Academia
Postgraduate studies and computational research
Data Engineering and Infrastructure
Cloud data engineering, ETL development, and big data architecture
Consulting and Professional Services
Data strategy, analytics advisory, and technology consulting
Technology Entrepreneurship
Starting data-driven ventures and commercialising analytics solutions
Fast-Track and Professional Pathways
Qualified students are eligible for accelerated pathways, including:
Industrial Training (SIWES)
- Supervised internships in data science, analytics, and technology organisations
Professional Certifications
- Preparation for certifications in cloud computing, data science, machine learning, and business intelligence
Research Pathways
- Supervised undergraduate research and progression to postgraduate studies
Entrepreneurship Incubation
- Access to innovation hubs, startup support, and technology commercialisation services
Industry Collaboration
- Partnerships with agritech, healthtech, fintech, and environmental technology organisations