Train Engineering Teams with Project-based AI Curricula

Turn talent debt into AI-ready teams capable of building and operating production AI systems.

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The tech we train on

Andela's AI curriculum

Train engineering teams across the AI application lifecycle including LLM engineering, agentic systems, production deployment, and AI leadership.

LLM Engineering

Build reliable, production-grade LLM applications

Implement RAG systems for information retrieval

Engineer prompts with reliability controls

Fine-tune models for specific use cases

Generate outputs for downstream integration

Interface showing LLM Engineering sections with progress: RAG Implementation 7 of 7 completed, Prompt Engineering & Safety 5 of 5 completed, Model Selection & Fine-tuning 2 of 5 completed, Structured Outputs 0 of 7 completed.

Agentic AI

Architect autonomous systems for complex workflows

Design architecture for agent systems

Build multi-agent systems for problem-solving

Create conversational flows for natural interactions

Integrate function calling capabilities

A progress tracker for Agentic AI Engineering course sections showing completion status for Architecture & Frameworks, Multi-Agent Systems, Conversational Flows, and Tool Integration.

AI In Production

Deploy scalable AI infrastructure in live environments

Deploy AI-optimized cloud architectures

Implement LLMOps and CI/CD pipelines

Monitor metrics and system performance

Manage security and governance

Mobile interface titled AI In Production showing progress on four modules: Deploy & Cloud Architectures fully completed, LLMOps & CI/CD fully completed, Observability & Monitoring partially completed, and Security, Governance, and Cost not started.

AI Strategy & Leadership

Drive AI strategy, alignment, compliance and adoption

Communicate strategy to stakeholders

Simplify complexities into actionable initiatives

Build AI roadmaps

Lead AI teams and drive adoption

A progress tracker for AI & Leadership course sections showing completion status: Strategic Stakeholder Comms 7 of 7 completed, Problem Decomposition 5 of 5 completed, Prioritization & Roadmapping 2 of 5 completed, and Leading AI Teams & Adoption 0 of 7 completed.

Our training creates compounding enterprise value.

Reduce talent debt, increase output

Prevent skill decay and build durable AI capability so teams deliver more with the same engineering capacity.

Turn PoCs into production faster

Teams are trained on the full AI delivery lifecycle, transforming prototypes into production systems.

Develop internal AI technical leaders

Upskill engineers to lead AI initiatives, set technical direction, and drive adoption across the organization.

Build long-term AI capability

Role-based tracks create a self-sustaining learning engine — growing professional, human, and long-term AI capability.

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Empowering the next generation of AI-native talent

Here's what AI Academy alumni have to say

I loved how hands-on and interactive the sessions were. I came away with practical strategies for structuring prompts, which boosted my productivity and creativity.

Clement W.

Senior Software Developer, Vibes

I learned how to code more efficiently while staying mindful of security and quality. [The AI Academy] already made a real difference in how I approach my day-to-day work.

Winnie R.

Software Engineer, Safaricom

Andela's clear, hands-on training made complex concepts easy to understand and apply. I highly recommend the program to any developer looking to boost their AI skills.

Emad S.

Senior QA Engineer, Wolters Kluwer

The AI Academy elevated my skills and confidence. The expert sessions, roundtables, and community support gave me practical knowledge and motivation to push my limits.

Wainaina K.

Senior QA Engineer, Dolby