Department of Data Science
School of Computing (SOC) • Federal University of Technology, Akure
About the Department
The Department of Data Science at the Federal University of Technology, Akure (FUTA) is a premier center for data science education and research within the School of Computing (SOC). Our department is dedicated to developing highly skilled data science professionals capable of extracting meaningful insights from complex datasets, building intelligent systems, and driving data-driven decision-making in organizations and society.
Data Science is an interdisciplinary field that combines mathematics, statistics, computer science, and domain expertise to extract knowledge and insights from data. Our comprehensive curriculum covers machine learning, statistical analysis, data mining, big data technologies, data visualization, artificial intelligence, and computational thinking. Students develop strong technical competencies through intensive theoretical study combined with practical experience using industry-standard tools and frameworks.
The department emphasizes hands-on learning with modern data science infrastructure including advanced computing labs, machine learning development environments, data visualization platforms, big data processing frameworks, and interactive analytics tools. We maintain strategic partnerships with leading technology companies, financial institutions, research organizations, and Fortune 500 companies, providing students with internship opportunities through SIWES and collaborative data science projects. Our faculty members conduct cutting-edge research in machine learning, artificial intelligence, data analytics, and emerging data science applications.
Our graduates are highly sought after by organizations worldwide. They demonstrate proficiency in data analysis, statistical modeling, machine learning implementation, data visualization, predictive analytics, and business intelligence. Graduates pursue rewarding careers in technology companies, financial institutions, healthcare organizations, government agencies, research institutions, and innovative startups, significantly contributing to data-driven transformation across industries.
What We Offer
Academic Programs
- B.Sc/B.Tech in Data Science - 4-year undergraduate program
- M.Sc in Data Science - Postgraduate studies
- M.Sc in Data Analytics and Business Intelligence - Specialized Masters
- Ph.D in Data Science - Doctoral research program
Specialized Areas
- Machine Learning and Deep Learning
- Statistical Modeling and Analysis
- Big Data Technologies and Analytics
- Data Mining and Knowledge Discovery
- Artificial Intelligence and NLP
- Data Visualization and BI
- Predictive Analytics
- Data Engineering and Database Systems
Laboratory and Computing Facilities
Machine Learning Lab
Python, TensorFlow, Keras, scikit-learn, and deep learning frameworks
Big Data Analytics Lab
Hadoop, Spark, NoSQL databases, data warehousing technologies
Data Visualization Suite
Tableau, Power BI, matplotlib, Plotly, and interactive visualization tools
Research Focus Areas
Our department conducts cutting-edge research in various data science domains:
Machine Learning and Deep Learning
Supervised and unsupervised learning, neural networks, convolutional networks, recurrent networks, transfer learning, ensemble methods.
Statistical Modeling and Analysis
Hypothesis testing, regression analysis, time series analysis, Bayesian methods, probabilistic modeling, experimental design.
Big Data Technologies
Distributed computing, MapReduce, Spark, Hadoop, stream processing, scalable algorithms, cloud data platforms.
Data Mining and Knowledge Discovery
Pattern discovery, clustering, classification, association rules, anomaly detection, feature extraction and selection.
Natural Language Processing and AI
Text mining, sentiment analysis, language models, information extraction, machine translation, conversational AI.
Data Visualization and Business Intelligence
Interactive dashboards, visual analytics, data storytelling, BI systems, real-time analytics, decision support systems.
Predictive Analytics and Forecasting
Time series forecasting, demand prediction, risk assessment, trend analysis, scenario modeling, causal inference.
Career Opportunities
Graduates of Data Science enjoy diverse and highly rewarding career paths:
Data Scientist
Machine learning, predictive modeling, data analysis
Data Analyst
Data exploration, reporting, business analytics
Data Engineer
Pipeline development, data infrastructure, databases
ML Engineer
Model development, deployment, system optimization
Business Intelligence Analyst
Dashboard creation, business insights, BI solutions
AI Researcher
Research, innovation, emerging technologies
Academic & Research
University lecturers, researchers, innovation
Data Consultant
Consulting, advisory, strategic analytics
Data Science Entrepreneur
Startup founder, analytics products, innovation
Admission Requirements
UTME Requirements
- Minimum UTME score of 160-180+
- Subject combination: English, Mathematics, Physics, Chemistry or Biology
- Five O'Level credits in two sittings maximum
- Credit passes must include: English Language, Mathematics, Physics, Chemistry or any other Science subject
Direct Entry Requirements (200 Level)
- Two A'Level passes in Mathematics and one of Physics/Chemistry/Further Mathematics
- ND/HND upper credit in Computer Science, IT, or related field
- OND with credit in relevant computing or mathematics-related disciplines
- Plus O'Level requirements as stated above
Course Materials & Resources
Find Your Materials in the General Library
All lecture notes, past questions, textbooks, and study packs for every level of Data Science now live in one place — the LEGACY General Library.
Go to General Library