Welcome to the AI4EAC Innovation Challenge Education stream. This stream is aimed at Intermediate AI practitioners; there is no specific prior knowledge needed, but an understanding of AI and machine learning tools will help you succeed.
We recommend that everyone starts with one of the foundational AI courses offered by Microsoft, Oracle or IBM SkillsBuild. After that, we have provided a selection of webinars and courses offered by our incredible network of partners, as well as practice challenges to help you build your skills in AI for Education and work towards the final challenge, an AI Education Challenge hosted on Zindi on 28-29 March.
Please explore the content available to you on this page - note that webinars are live events, while courses are always available. Practice Challenges and office hours will become available later in the Programme. There are no course requirements for participation in this programme - the content is freely available to all. Certificates will be awarded at the end of the programme based on your level of participation.
Courses
Machine Learning: Data Preparation and Feature Engineering
Provider: GIZ
This self-paced course is for learners with basic ML knowledge who want to strengthen their data skills. You'll learn how data quality and size affect models, plan realistic data prep timelines, collect and build datasets, handle imbalanced data, split samples correctly, and transform numerical and categorical features within the ML workflow.
Managing and Evaluating AI Projects
Provider: GIZ
This course introduces the concepts of evaluating and managing artificial intelligence projects.
What to know to get started with Zindi Challenges
Provider: Zindi
Learn how to get started with participating in Zindi Challenges.
Artificial Intelligence for All: How to eliminate or mitigate biases in Artificial Intelligence training data
Provider: GIZ
This course focuses on addressing practical challenges to AI training data in African countries as a way of strengthening local actors in the field of AI through locally developed learning content. This course is about building open, locally relevant, and unbiased AI training data for AI practitioners in Africa.
