Course Overview/description:

    H3ABioNet is planning to host a 5-day, in-person workshop, which will take place in Cape Town from 23-27 October 2023. During this workshop we aim to teach participants how to implement the various components of our popular “Multiple-Delivery-Approach Learning Model” within their regions/projects. The workshop will cover several themes from designing your training for a blended/distributed classroom model, to best practices for administrative processes and managing distributed cohorts. The workshop will be incredibly hands-on, and will assume some familiarity with training models and processes, but would be best suited to those who aim to implement the model and have the capacity to do so.

    Keywords: Education, Blended learning, Training, Train-the-Trainer

    Skill level of training: Introductory

    Language: Course is offered in English

    Credential awarded: Workshop certificate

    Type of training: face-to-face – course will run in person in Cape Town, South Africa

    Dates for the workshop: 22 – 27 October 2023; 9 am - 5pm

    Workshop organizers: Verena Ras, Shaun Aron, Sindiswa Lukhele, Tshinakaho Malesa, Pertunia Mutheiwana, Sumir Panji, Nicola Mulder

    Registration opens:  This is a closed training event. Participation by invitation only!

    Workshop Sponsors: H3ABioNet

    Intended Audience: The course will be aimed at those who have recently completed the WCS/H3ABioNet/Elixir/EBI TtT course in 2022 OR the applicant must show a strong willingness and desire to deliver bioinformatics training in their region and be able to run the model post training. Must also be in a position where they can implement the model immediately i.e. should preferably have a staff position. 

    Syllabus and Tools:

    Currently being finalised


    • Completed a previous TtT course/workshop OR, in possession of other training qualification/certificate i.e. able to demonstrate interest in and knowledge of training theory (essential)
    • Experienced in bioinformatics or related sub-discipline e.g. computational biology, molecular biology, biostatistics, informatics etc. (essential)
    • Currently designing/implementing training – either short or long term, degree and non-degree programmes (essential)
    • Ability to implement regional training programmes (preferable)

    Learning objectives/outcomes:

    On completion of the course, participants should be able to:

    • Be able to plan and  implement a regional training event using the IBT model across multiple/parallel classrooms
    • Be able to setup a Learning Management Site and know  how to effectively use it as a training tool
    • Be able to design effective communication strategies for large scale training
    • Be able to design the various components of a large scale, blended learning training
    • Be able to manage administrative processes as it pertains to large scale regional trainings

    Workshop limitations: This workshop will only provide participants with the skills to initiate their own distributed learning model training. The workshop will not make provision for ongoing use of tools like learning management sites etc. and participants are encouraged to investigate resources that are easily available and accessible within their own regions/countries.

    Licensing for course materials: Course material information will be made available in due course.

    Course Overview/description:

    Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover an introduction to The Shell, Python and R. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

    Keywords: Carpentries, programming, coding, novice, R, Python, linux 

    Skill level of training: Beginner  

    Language: English

    Venue of workshop: Online via Zoom; link will be communicated to those who are accepted.

    Dates for the workshop: 14 - 18 March 2022 from ~10 am – 2:30 pm all days

    Registration opens:  02 March 2022 | Registration closes: 09 March 2022 | Notification date: 10 March 2022

    Link to application form: This is a closed workshop aimed at students and staff at the Faculty of Health Sciences at the University of Cape Town.

    Workshop trainers: Lyndon Zass, Ruth Nanjala, Verena Ras, Ichrak Benamri, Nihad Alsayed, Melek Chaouch, Ziyaad Parker, Mamana Mbiyavanga 

    Workshop organisers: H3ABioNet, Verena Ras, Lyndon Zass, Nicola Martin, Darren Martin

    Workshop Sponsors: H3ABioNet

    Intended Audience: UCT Computational Biology Honour’s cohort + anyone else from within UCT Health Sciences who may be interested

    Syllabus and Tools: please see workshop website:

    Prerequisites: As this is presented at a novice level, no prerequisites are required but you will need to have access to a laptop where you are able to install the required software (R, Python, shell terminal). You will also need good internet access to ensure you are able to be online for the full course.

    Workshop limitations: This workshop will only provide a foundation in Linux, R and Python but will not teach any advanced coding or programming. Should this be what you require, this may not be the appropriate course for you.


    Training Materials Availability:

    Training materials used for this course were not directly produced by H3ABioNet but may be accessed here: Please note, these materials may be governed by different sharing/re-use policies, and you are encouraged to follow the policies of the external providers regarding material re-use and/or sharing.

    Course Overview: The Research Data Management (RDM) short course introduces the principles and practices of RDM and practical advice for implementing these practices in African research context. Topics covered include data discovery and re-use, data documentation and organization, data standards and Ontology, data storage and security, repositories and policies, FAIR & reproducibility and best practices in developing an effective DMP.

    Intended Audience: The course is aimed at the graduate students and biomedical scientists who are currently working on clinical, genomics and bioinformatics projects in Africa.


    Venue of course: Online through Zoom.

    Dates for the course: 27-30 June 2022; from 10:00 CAT to 14:00 CAT.

    Course organizers: Faisal Fadlelmola, Katherine Johnston, Verena Ras, Melek Chaouch, Lyndon Zass, Ziyaad Parker, Ayton Meintjes, Sumir Panji and Nicola Mulder

    Participation: The course is available to any participant who is able to attend the Zoom sessions and the interactive hours with the course instructors for the days of the course.

    Course Sponsors: H3ABioNet

    Participant applications

    Registration for participants opens:  4th April 2022

    Registration for participants closes: 24th April 2022

    Notification date for successful Applicants: 6th  June 2022

    Link to participant application form: Click here


    Course Curriculum:

    Module 1: Data & research life cycle

    Module 2: Curation, data types and privacy issues

    Module 3: Standards, taxonomy & Ontology

    Module 4: Preservation, repositories, security and policies

    Module 5: FAIR & Reproducibility

    Module 6: Data Management Plan (DMP)


    Course Schedule:


    Session 1

    10:00-11:00am CAT

    Session 2

    11:00-12:00am CAT  

    Session 3  

    12:00-1:00pm CAT

    Interactive hour with Instructor/s 

    (1:00-2:00PM CAT)


    27 June 2022

    Module1: Lecture

    Module 2: L1

    Module 2: L2

    Faisal; Katherine & Verena

    Tuesday 28 June 2022

    Module 3: Lecture

    Module 4: L1

    Module 4: L2

    Lyndon & Verena;  Ayton and Ziyaad


    29 June 2022

    Module 5: Lecture

    Module 5: FAIR Tutorial


    Melek & Ziyaad


    30 June 2022

    Module 6: Lecture

    Module 6: DMP Tutorial - Group A

    Module 6: DMP Tutorial - Group B

    Faisal; Ayton


    Prerequisites: A basic background/understanding of biochemistry, molecular biology and/or genetics. Those with a computer science background with experience in bioinformatics are welcome to apply.

    Objectives: After this RDM short course participants should be able to:

    1. Understand what research data management is;
    2. Recognize why research data management is necessary;
    3. Understand best practices and aspects for research data management; and
    4. Have knowledge of the RDM tools available at your institution and online.

    Course limitations: This course will only provide a foundation for continued learning in research data management and will not teach any advanced RDM aspects.

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