Course overview
A practical pathway built around a clear outcome.
Use AI tools responsibly for learning, communication and enterprise work while checking evidence.
Design a safe, documented AI-assisted workflow for an agricultural use case.
Department of Digital Agriculture and Technology
Responsible AI for African Agriculture
Use AI tools responsibly for learning, communication and enterprise work while checking evidence.Entry qualifications
Who this course is for
- Young people, farmers, professionals or enterprise builders working in or entering agriculture.
- Basic English reading ability and access to an internet-enabled phone or computer.
- No prior university qualification is required for Foundation courses.
- Professional and Advanced courses benefit from relevant field, study or enterprise experience.
Learning objectives
What you will build
- Apply prompt design to a defined agricultural context.
- Apply verification to a defined agricultural context.
- Apply responsible use to a defined agricultural context.
- Produce evidence of learning through practical assignments and assessment.
Course structure
Learn. Apply. Demonstrate.
Learn
Accessible lessons, African examples, transcripts and guided resources.
Apply
Practical exercises connected to a real farm, enterprise or community question.
Demonstrate
Assessments and a useful final output aligned to the stated course outcome.
Beyond learning
Move from course progress to live opportunity.
See verified calls mapped to this course and Department. Expired opportunities are archived automatically.