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Big Data and Data Science Training

The Regional Hub for Africa aims to use this page to keep the African data science community informed of up-coming training courses, as well as to share already established (reputable) training courses, and signpost the tools and frameworks that are available to support an individual's continuous professional development.

Please ensure that you have discussed your learning requirements with your manager and that you have the appropriate approvals in place prior to undertaking any new training.

Available (Reputable) Training and Mentoring programmes

  • UN Learning Management System – holds free (short) online Big Data courses, developed by the various UN-CEBD Task Teams on Big Data. More free online courses are due to be added soon. You need to register first (free) before accessing the courses.
  • UNSIAP Learning Management System (ESCAP) – holds facilitated e-learning and self-paced e-learning courses. You need to register first (free) before accessing the courses.
  • International Data Masterclass – Available on the UN Learning Management System (online and free). The International Data Masterclass has been designed to help non-analytical senior leaders across world-wide governments to put data and evidence at the heart of their decision-making.
  • International Data Science Accelerator (Mentoring) Programme - is a short-term virtual mentoring programme involving mentors and mentees from global National Statistics Offices and international organisations. The programme is project focused and it prioritises National Statistical Offices (NSOs) in low and middle-income countries who are looking at developing their data science capability.  Mentee applicants need to identify a small project within their business area that may be solved using non-traditional data sources or new data science tools and techniques. If you are interested in applying, please contact the Data Science Campus at ONS for more information via International.data.science.accelerator.programme@ons.gov.uk

Big Data Training Catalogue

The UN Task Team on Training, Competencies and Capacity Development has developed the UN Big Data Training Catalogue. This can be used to:

  • Search its (global) training database for available training courses (not all are free)
  • Create your own Learning Pathway that outlines your personal development and training needs
  • Peruse the Big Data Competency Framework to consider the knowledge, skills and attributes required to work with Big Data
  • Apply the Big Data Maturity Matrix to your Big Data project to understand the gaps and how to fill them (this is due to be updated to V2.0 soon)

New Training announcements

New training announcements will be made here.

Expired Training

UN SIAP: Principles of Reproducible Analytical Pipelines for Official Statistics

The UN Regional Hub for Big Data and Data Science for Africa is pleased to announce that colleagues at UN SIAP will be delivering an e-Learning course Principles of Reproducible Analytical Pipelines for Official Statistics from 17 February to 14 March 2025, for African Members States. The e-learning course aims to build capacity in national statistical systems for the development and implementation of Reproducible Analytical Pipelines (RAPs) for Official Statistics (in other words, automating a statistical process using open source software, such as R). The following attachments provide more detailed information on the course:

1. Invitation letter

2. Concept Note

The course will be delivered via 5 x one-hour webinars, with weekly assessments and a practical element. The total commitment is estimated as 12-15 hours. A Certificate will be shared with those who achieve a pass (at least 70%). Since this course has a practical goal that will use R programming, a mandatory tutorial is required for participants to complete before being able to access the course.

DGs are invited to circulate this invitation across their organizations and nominate participants, who are deemed qualified for this course. Please note that the course will be delivered in English - this includes all instruction, materials, communication, and exercises.

Applicants are kindly requested to fill out the nomination form at the following link: https://forms.office.com/e/0ttdEff9pt

The deadline for receipt of nominations is Thursday 13 February 2025.

Our thanks are extended to Christophe Bontemps at UN SIAP for offering this learning opportunity.

Please obtain the relevant authorisation from within your organisation prior to enrolling on this course