Available courses

This course aims to teach the following topics:

  • Introduction to data visualization
  • Data visualization techniques
  • Data visualization tools
  • Issues in data visualization


This course aims to teach the following topics:

  • Use essential OpenRefine functionality
  • Advanced OpenRefine functions
  • Reference resources for further learning


This course aims to teach the following topics:

  • How to collect, share, store, and protect the sensitive data
  • understand the principles of good research data management
  • GDPR and data protection regulations, and what these mean for research and research data
  • Relevant services and resources available to researchers at the university


This course aims to teach the following topics:

  • Preservation needs of research data
  • Introduce the concepts of authenticity and integrity
  • Identify the different types of metadata and their role in data discovery and reuse
  • The role of trustworthy repositories 
  • How repositories demonstrate their trustworthiness through audit and certification


This course aims to teach the follwing topics:

  • Benefits and challenges of sharing research data
  • How to protect the confidentiality 
  • How data ownership can affect data sharing
  • Different types of access restrictions
  • How to enable data sharing through the application of a standard license


This course aims to teach the following topics:

  • Strategies for organizing research data such as versioning,  file naming conventions and data file formatting and transformations
  • Why documenting data and data citation are important.
  • Issues involved in storing, securing, and backing up research data


This course aims to teach the following concepts:

  • Components of good DMP
  • DMP policies of several funding agencies
  • Information on data management planning tools.


The course aims to teach the following topics:

  • Research data in an array of contexts
  • Data management concepts: 1.metadata; 2.research data lifecycle. 
  • Concept of data management: 1. identify the roles and responsibilities of key stakeholders; 2. examine various data management tasks throughout the research data lifecycle.



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