PROGRAM
Skills assessment
A clear-eyed read on where your team is today and the exact gap to close.
- Production-aware
- Reviewed with evidence
AI Capacity Building
Turn your team into AI builders.
Not another slide deck. Omdena's capacity-building programs upskill your people by shipping real AI on real data, mentored by senior engineers, so the capability stays in-house long after we leave.
Hands-on
Project-based learning
In-house
Capability that stays
LEARN BY SHIPPING
Real projects - senior mentorship - your tooling, capability that outlasts the engagement.
What's in a program
Built around your team and your data.
PROGRAM
Custom curriculum
A program designed around your stack, your data and your business goals.
- Production-aware
- Reviewed with evidence
PROGRAM
Real-project sprints
Cohorts ship a working AI deliverable on a problem that matters to you.
- Production-aware
- Reviewed with evidence
PROGRAM
Senior mentorship
Experienced Omdena engineers guide every sprint, review and decision.
- Production-aware
- Reviewed with evidence
PROGRAM
Tooling and MLOps
The practical workflow: version control, evals, deployment, not just theory.
- Production-aware
- Reviewed with evidence
PROGRAM
Responsible AI
Fairness, safety and governance baked into how the team learns to build.
- Production-aware
- Reviewed with evidence
PROGRAM
Leadership briefings
Decision-maker tracks so leaders can scope, fund and govern AI well.
- Production-aware
- Reviewed with evidence
PROGRAM
Certification
Recognized completion that maps to demonstrated, project-based capability.
- Production-aware
- Reviewed with evidence
How it runs
A cohort that ships, not just studies.
Your people work in a mentored cohort on a project that matters to your organization. By the end they have shipped something real and learned the workflow, tooling and judgement to do it again.
WHAT THIS MAKES PRACTICAL
Problem framingData pipelinesModel trainingEvalsDeploymentMLOpsResponsible AICode review
FLOW - assess - build - embed
01
Assess
Skills audit, goals, target capability
02
Design
Curriculum, project, cohort, schedule
03
Build
Mentored sprints on real data and tooling
04
Embed and certify
Handover, standards, certification
Who it's for
Teams that want capability, not dependency.
Enterprise AI teams
Level up engineers and data scientists so they ship production AI in-house.
Government and public sector
Build sovereign AI capability inside agencies and ministries.
NGO and impact data teams
Equip mission-driven teams to use AI responsibly on their own data.
Reskilling and mobility
Move analysts and adjacent talent into applied ML and AI roles.
Universities and academies
Project-based AI tracks that produce job-ready graduates.
Centres of Excellence
Seed the skills, standards and tooling an internal AI CoE runs on.
A simplified process, powered by Umaku
Explore the platform From skills gap to shipped capability.
01
Assess
Umaku captures the target capability, current skills and constraints as structured scope.
02
Design
We co-design the curriculum, cohort and a real project around your goals and data.
03
Review
Four AI agents review every commit for scope, quality, DevOps, and bugs, with evidence.
04
Mentor and ship
The cohort builds in mentored sprints and ships a working, reviewed deliverable.
05
Embed and certify
Standards, tooling and documentation are handed over; participants certify on real work.
Outcomes
Capability that stays in the building.
Applied
People practice on real AI workflows instead of passive slideware.
1 project
A real deliverable your team owns, produced during the program itself.
In-house
The workflow, tooling and judgement to keep building after the engagement ends.
Related case studies
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Combining satellite imagery, demographic, and infrastructure data to prioritize rural electrification investments.
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Computer Vision · HealthBattling Malaria in Liberia with AI
Smart diagnostic and surveillance tools supporting field workers in low-connectivity environments.
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NLP · Public SectorAI to Combat Misinformation & Disinformation
Multilingual NLP pipelines that detect coordinated narratives and surface verifiable signals.
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Predictive ML · MobilityShort-Term Traffic Congestion Prediction
Spatio-temporal models that forecast congestion and inform city operations in near real time.
Read case studyWhat is AI capacity building?
AI capacity building helps organizations develop the internal knowledge, workflows, governance, and implementation capabilities required to successfully adopt AI across operations and teams.
How is this different from traditional AI training?
Unlike traditional AI courses focused only on theory, Omdena combines AI education, collaborative development, real-world implementation, and operational adoption support.
Do teams need prior AI experience?
No. Programs are designed for both technical and non-technical teams, including leadership, operations, and engineering stakeholders.
What industries does Omdena support?
Omdena supports enterprises, NGOs, startups, governments, and innovation teams across climate, energy, healthcare, agriculture, supply chain, finance, and public sector domains.
Can Omdena help identify AI use cases for our organization?
Yes. AI use case discovery and roadmap development are core parts of the engagement.
Does Omdena support implementation after training?
Yes. Omdena supports organizations through AI prototyping, implementation, workflow integration, governance, and long-term adoption support.
How long does an AI capacity building engagement take?
Programs can range from focused workshops and short-term enablement programs to multi-phase AI adoption and implementation partnerships.
Build the team, not just the model.
Get a consultation and we will design a program around your team and goals.
Design a program