How is this course delivered?

This is a tutor-led course delivered live online, taught in English (Uganda). Your tutor guides you through the curriculum live rather than leaving you to self-study pre-recorded videos.

Will I get a certificate?

Yes. You'll receive a course 24: ai for education certificate of completion after completing the course requirements.

What do I need to know before I start?

You should have: Completion of course:Supervised Learning in Depth; Completion of course: Recommender Systems.

How long does the course take, and what does it cost?

The course runs for 6 weeks and costs UGX 550,000. Paying for one programming course also unlocks 25% off your next one.

What do I need to have ready to join?

You'll need: Computer; Reliable internet connection; Modern web browser; Python 3; Jupyter Notebook or Google Colab; pandas; scikit-learn; Streamlit or another simple dashboard tool; Spreadsheet software; Institution-approved generative AI tool.

Can I get help if I get stuck?

Yes. Enrolled students can book one-on-one tutor sessions any time through Get Help, in addition to regular class time.

Programming UniversityAI for Education

Machine Learning

University

AI for Education

Duration

6 weeks

Investment

UGX 550,000

Certificate

Included

Teaching

Live online

Enroll in this tutor-led course Get Help

Program Introduction

AI for Education is an intermediate programme for educators, school leaders, curriculum teams, education data practitioners and EdTech developers in Uganda, East Africa and Africa. Learners explore how artificial intelligence can support personalised learning, learning analytics, assessment, content tagging and evidence-informed educational decisions. The programme emphasises privacy, fairness, transparency, data quality and human oversight.

Key Features & Benefits

• Uganda and African education context • Practical educational data projects • Adaptive learning and recommendation systems • Student-risk prediction and learning analytics • Automated grading and AI-assisted feedback • UNEB-aligned content tagging practice • Responsible AI, privacy, bias and human oversight • Capstone AI-assisted learning tool

Real-World Applications

• Personalise learning content and pathways • Identify learners who may need early academic support • Generate quizzes and question banks for teacher review • Support marking and feedback workflows • Tag and analyse learning content against Ugandan subject and assessment contexts • Build student-performance dashboards • Prototype AI-assisted learning tools for schools and EdTech platforms • Use learning analytics to support education planning

Course outline and learning expectations

This is a tutor-led course. The outline shows what your tutor will cover; teaching materials and examinations are provided directly to enrolled students.

AI for Education UgandaAI Education Course UgandaAI Training for Educators UgandaEdTech UgandaEducation Technology East AfricaAI in Education East AfricaAI Education AfricaLearning Analytics AfricaAdaptive LearningStudent Performance PredictionAutomated GradingAI Quiz GenerationUNEB Content AnalyticsResponsible AI in Education

Teaching format

Live online

Teaching language

English (Uganda)

Intended learners

University

What you will learn

Explain how AI is reshaping education globally and in African learning contexts
Evaluate adaptive learning systems and how they personalise educational content
Prepare and analyse student data for performance and dropout-risk prediction
Build and assess a simple student-performance prediction model
Design automated grading and feedback workflows with teacher oversight
Build a basic recommendation engine that suggests the next topic to study
Generate and review AI-assisted quizzes and questions for accuracy and curriculum relevance
Tag learning content for UNEB-related subjects and interpret learning analytics
Apply responsible AI principles including privacy, fairness, transparency and human oversight
Develop a capstone AI-assisted learning tool or dashboard

Modules

1
AI and the Changing Education Landscape
Examine how AI is reshaping learning, teaching and assessment globally, with attention to Uganda and Africa.
AI in education overviewGlobal and African trendsOpportunities and limitationsResponsible use and human oversight
2
Adaptive Learning Systems
Explore how adaptive systems use learner data to personalise content and learning pathways.
Learner profilesContent personalisationAdaptive pathwaysEquity and accessibility
3
Student Performance and Dropout-Risk Prediction
Use educational data to explore early-warning models while avoiding harmful labelling.
Educational data preparationFeatures and targetsClassification basicsModel evaluationFairness and privacyHuman review
4
Automated Grading and Feedback
Design AI-supported grading and feedback workflows that keep teachers in control.
RubricsObjective-item gradingFeedback generationQuality assuranceBias and error checks
5
Learning Recommendation Engine
Build a simple engine that recommends what topic a learner should study next.
Recommendation logicMastery indicatorsRule-based and basic data-driven approachesTesting recommendations
6
AI-Powered Quiz and Question Generation
Generate, review and improve questions for learning and assessment.
Prompt designQuestion typesDifficulty levelsAnswer keysFact-checkingTeacher approval
7
UNEB-Aligned Content Tagging and Analytics
Tag learning materials and assessment items against relevant Ugandan subject and competency categories.
Content taxonomySubject and topic tagsCompetency tagsAssessment analyticsDashboard indicators
8
Capstone: AI-Assisted Learning Tool
Develop and present a practical prototype for an African education context.
Problem definitionData and privacy planModel or rulesUser interfaceTestingDocumentationPresentation