Multidisciplinary Studies / Data and Information Science


Degree awarded:
  • M.I.R.M
  • M.Inf.Sc
  • M.Phil
  • M.Phil/Ph.D
  • Ph.D
  • Master of Information Science (M.Inf.Sc)
  • Master of Information Science (M.Inf.Sc.)
  • Master of Information Science
Field of interest:
  • corporate knowledge Management
  • Database Design and Administration
  • Economics of Information
  • Information Management Practice
  • Information Policy
  • Information Systems
  • Informetrics
  • Internet Technology
  • Knowledge Management
  • Not Applicable
  • Organization and Retrieval of Information
  • Science and Technology Studies
  • Social Informatics
  • Speech and Language Technology
  • Web Application Development
Entry requirements:

    General Regulations Governing Admission to Higher Degree Programmes

    • Candidates for admission to higher degree programmes shall normally be graduates of the University of Ibadan or other Universities/Institutions recognised by the Senate. Admission shall be made by the Postgraduate College on the recommendation of the appropriate Faculty Postgraduate Committee.
    • Candidates without any previous higher degrees in the relevant discipline may be admitted only to either the Degree of Master or the Professional Degree of Master.
    • Candidates with recognised “Research Higher” Degree in the relevant discipline may be admitted to the M.Phil or Ph.D. degree programmes as appropriate, on the recommendation of the appropriate Faculty Postgraduate Committee.
    • A candidate admitted to the degree of Master of University of Ibadan who obtained a weighted average mark of 55.0 – 59.9%, or a CGPA of between 4.0 and 4.9 may be offered provisional admission to the M.Phil./Ph.D programmes. Such candidates shall be assessed within three semesters of full time and four semesters of part time registration for the M.Phil/Ph.D to Ph.D conversion. This shall also apply to students who graduated from other universities    


    • All University of Ibadan graduates should be admitted to Postgraduate programme with the ordinary level criteria existing at the time their first admission. Candidate who did not fulfill the requirements as at the time of their admission are not eligible for consideration.
    • Special consideration may be given to candidates, who obtained their first degree not less than 20 years from the time of seeking admission to any postgraduate programmes. Such candidates must have been found to possess special skills or abilities and professionally or academically engaged during the period of 20 years.
How to apply:
Apply online

Our Data and Information Science programme is an interdisciplinary field that focuses on the collection, management, analysis, and interpretation of data to derive valuable insights and support decision-making processes. We combine elements of computer science, statistics, information systems, and domain knowledge to impact meaningful information to our students. Here is a summary of the course overview for Data and Information Science:

Data Collection and Management: 

  • This course introduces students to various methods of data collection, including surveys, experiments, observations, and data mining. They learn about data quality, data cleaning, data integration, and data storage techniques. Students also gain an understanding of data governance and ethical considerations in data management.

Data Analysis and Visualization: 

  • This course covers statistical techniques and data analysis methods used to extract insights from data. Students learn about data exploration, descriptive statistics, inferential statistics, and data visualization techniques. They also gain hands-on experience with data analysis tools and software.

Machine Learning and Predictive Analytics: 

  • This course focuses on machine learning algorithms and techniques used to build predictive models from data. Students learn about supervised and unsupervised learning methods, feature selection, model evaluation, and model deployment. They explore applications of machine learning in various domains.

Big Data Analytics: 

  • This course addresses the challenges and opportunities associated with analyzing large and complex datasets known as big data. Students learn about distributed computing frameworks, such as Hadoop and Spark, and technologies for processing and analyzing big data. They also study data streaming, real-time analytics, and data visualization for big data.

Information Retrieval and Search Engines: 

  • This course explores techniques for retrieving and organizing information from large collections of data. Students learn about indexing methods, information retrieval models, search engine algorithms, and relevance ranking. They gain an understanding of how search engines work and how to improve search performance.

Data Privacy and Security: 

  • This course focuses on the ethical and legal considerations in handling data, as well as methods for ensuring data privacy and security. Students learn about data protection regulations, encryption techniques, access control mechanisms, and risk management strategies. They explore techniques for anonymizing and de-identifying data.

Data Ethics and Governance: 

  • This course examines the ethical implications of data collection, analysis, and use. Students explore ethical frameworks, privacy concerns, bias and fairness issues, and the responsible use of data. They also learn about data governance frameworks and strategies for managing data assets within organizations.

Data Science Capstone Project: 

  • In the capstone project, students apply their knowledge and skills to a real-world data science problem. They work in teams or individually to define a problem, collect and analyze relevant data, and develop data-driven solutions or recommendations. The project allows students to showcase their abilities and gain practical experience in data science.

Few/Some of the Course Content


FSC 701Introduction to Information Science and Theory
IRM 702Research and Quantitative Methods for Information Professionals
FSC 715Organization of Data and Information Sources 
IRM 717Online Searching
FSC 721Information Systems Analysis, Design and Evaluation
FSC 724Database Management Systems I
FSC 731Information Users, Sources and Systems
FSC 736Technical Writing and Presentation
FSC 741Management of Information Resources 
FSC 755Information Technologies
IRM 794Industrial Attachment 
IRM 799Seminar Paper
IRM 747Corporate Knowledge Management
IRM 762Content Management
IRM 775Information Architecture and Knowledge Organization
IRM 772Intellectual Asset Management
IRM 766Information Security
FSC 746Management Information and Decision Support Systems
FSC 757Introduction to Artificial Intelligence and Expert Systems
FSC 723Introduction to Programming
FSC 751Productivity Software Skills Development
FSC 744Design and Marketing of Information Products
FSC 701Introduction to Information Science and Theory

Entry Requirement


Career Path

Graduates of our Data and Information Science programmes have a wide range of career opportunities in various industries. Some potential career paths include:

Data Scientist: 

  • Graduates can work as data scientists, analyzing and interpreting complex datasets to extract insights and support decision-making processes. They develop and implement machine learning models, conduct statistical analyses, and communicate findings to stakeholders.

Data Analyst: 

  • Graduates can work as data analysts, focusing on collecting, cleaning, and analyzing data to identify patterns, trends, and correlations. They use statistical techniques and data visualization tools to present data in a meaningful way and provide actionable insights.

Data Engineer: 

  • Graduates can work as data engineers, responsible for designing and building data infrastructure and systems. They develop data pipelines, design databases, and ensure data integrity, availability, and security. They also work closely with data scientists and analysts to enable efficient data processing and analysis.

Business Intelligence Analyst: 

  • Graduates can work as business intelligence analysts, responsible for gathering, analyzing, and presenting business-related data to support strategic decision-making. They create dashboards, reports, and visualizations to communicate key performance indicators and business metrics.

Data Consultant: 

  • Graduates can work as data consultants, providing expertise and guidance to organizations on data-related matters. They assess data needs, design data strategies, and help organizations leverage data for improved performance and decision-making.

Data Governance Specialist: 

  • Graduates can work as data governance specialists, focusing on establishing and implementing data governance frameworks and policies. They ensure compliance with data regulations, define data standards, and oversee data management processes within organizations.

These are a few examples of the career paths available to graduates of Data and Information Science programs. The field is rapidly growing, and there is a high demand for professionals who can effectively manage and analyze data to drive insights and innovation.



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