Level Up Your Career with
AI Literacy & Mastery Skilling

Join a cohort of technologists upskilling through AI-intensive, hands-on training with Andela’s AI Academy.
Increase earning potential by 20-40%
Access to F500 job opportunities
Production-ready expertise
Apply to AI Academy
Course progress for LLM Engineering with sections: RAG Implementation 7/7 completed, Prompt Engineering & Safety 5/5 completed, Model Selection & Fine-tuning 2/5 completed, Structured Outputs 0/7 completed.
Course progress for Agentic AI Engineering showing completed units in Architecture & Frameworks, Multi-Agent Systems, partial progress in Conversational Flows, and none in Tool Integration and Function Calling.
List titled AI In Production showing completion status of four topics: Deploy & Cloud Architectures 7 of 7 completed with AWS logo, LLMOps & CI/CD 5 of 5 completed with Docker logo, Observability & Monitoring 2 of 5 completed with Grafana logo, and Security, Governance, and Cost 0 of 7 completed.
Task list under AI & Leadership / FDE with completion statuses: Strategic Stakeholder Comms 7 of 7 completed, Problem Decomposition 5 of 5 completed, Prioritization & Roadmapping 2 of 5 completed, Leading AI Teams & Adoption 0 of 7 completed.
4.7/5
Star iconStar iconStar iconStar iconHalf star icon
Student reviews rating
The tech we train on
LangChain logo with a bird silhouette and a chain link icon next to the text LangChain.
GitHub brand name with the Octocat mascot icon, representing the GitHub platform.
Cursor company logo with a cube icon on the left and the word CURSOR in uppercase letters.
Windsurf company logo with stylized W symbol and text.
Claude company logo
GitHub Copilot
OpenAI
Pinecone company logo featuring a circular design of stylized pinecone shapes.
Hugging Face brand logo.
LangChain logo with a bird silhouette and a chain link icon next to the text LangChain.
GitHub brand name with the Octocat mascot icon, representing the GitHub platform.
Cursor company logo with a cube icon on the left and the word CURSOR in uppercase letters.
Windsurf company logo with stylized W symbol and text.
Claude company logo
GitHub Copilot
OpenAI
Pinecone company logo featuring a circular design of stylized pinecone shapes.
Hugging Face brand logo.

Two learning tracks to stay competitive in the age of AI

A new generation of engineering work has emerged. It calls for stronger foundations, deeper systems thinking, and fluency with AI.

AI FOUNDATIONS
Master foundations like AI-assisted coding & Kubernetes
Three-dimensional geometric shape resembling a cube with triangular faces in shades of gray and white.
Learn more about AI Foundations
AI ENGINEERING
Become an AI Engineer or Forward Deployed Engineer
Stylized dark brown cursive letter C on a white background.
Learn more about AI Engineering
Google logo with blue, red, yellow, and green colors.
NVIDIA logo
Kubernetes logo featuring a white ship wheel inside a blue hexagon.
AWS logo with orange arrow forming a smile under letters.
Microsoft Azure logo
Meta company logo.
LEARNING PARTNERSHIPS
Master the tech powering the AI revolution

Programs designed with industry leaders for real-world engineering

AI foundation courses

Strong foundations come first. These courses focus on AI-assisted workflows and the systems that support modern, scalable software.

AI Assisted Coding

Increase momentum in your development workflow

Progress list showing Prompt Engineering completed 7 of 7, Model Context Protocol (MCP) completed 5 of 5, AI-Augmented Coding Workflows completed 2 of 5, and Secure & Responsible Use of Copilot completed 0 of 7.
Kubernetes

Lay the groundwork for building and operating AI at scale

List of Kubernetes courses showing progress: Kubernetes Architecture & Core Concepts completed 7 of 7, Container & Cloud-Native Fundamentals completed 5 of 5, Networking, Security & Observability Basics completed 2 of 5, Kubernetes in the DevOps Lifecycle not started.

Turn an idea into working software faster.

Reduce the distance between intent and implementation.

Operate modern systems with confidence.

Build fluency in the infrastructure behind scalable software & AI.

Shift your time toward design and judgment.

Reduce time spent on translation, syntax, and repetitive work.

Build skills you can use anywhere.

Apply across codebases and production environments.
Apply to AI Academy

AI engineering curriculum

Learn to build and operate AI in the real world. This curriculum develops the engineering depth required to design, deploy, and run AI systems in production.

LLM Engineering

Build reliable, production-grade LLM applications

List of course modules with completion status: 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, LLM Hackathon 0 of 7 completed.
Agentic AI

Architect autonomous systems for complex workflows

List of progress in learning modules: Architecture & Frameworks 7 of 7 completed with hugging face icon, Multi-Agent Systems 5 of 5 completed with C icon, Conversational Flows 2 of 5 completed with red crown icon, Tool Integration and Function Calling 0 of 7 completed, and Agentic Hackathon 0 of 7 completed.
AI in Production

Deploy scalable AI infrastructure in live environments

List of course modules with completion status: Deploy & Cloud Architectures 7/7 completed with AWS logo, LLMOps & CI/CD 5/5 completed with Docker logo, Observability & Monitoring 2/5 completed with Grafana logo, Security, Governance, and Cost 0/7 completed, and AI Production Hackathon 0/7 completed.
AI Leadership & Strategy

Drive AI strategy, alignment, and adoption

Progress list showing completed tasks in Strategic Stakeholder Comms, Problem Decomposition, and partial completion in Prioritization & Roadmapping, with no progress in Leading AI Teams & Adoption and Critical Evaluation & Judgment.

Take responsibility for AI systems that matter

Operate with the judgment and rigor required when AI impacts customers, revenue, and risk.

Navigate complexity across models, systems, & teams

Work effectively where technical depth, product needs, and real-world constraints meet.

Turn AI ambition into working systems

Bridge the gap between experimentation and durable, real-world outcomes.

Earn trust as an AI technical leader.

Communicate tradeoffs clearly, guide decisions under uncertainty, and lead adoption across teams.
Apply to AI Academy
Explore Curriculum

Continuous assessments & 
real-world learning

Andela’s approach to assessments & learning moves beyond event-based certifications and classroom-style instruction.

Assessment Learning Assess Curriculum design Real-world project Peer mentoring Learning phase Validate

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
Apply to AI Academy

Explore the AI 
engineering curriculum

Program logistics
10 weeks

Program Duration

40h/week

Time Commitment

Online

Format

Who this curriculum is for
8+ years in software engineering, data science/ engineering, AI/ML engineering, or cloud/DevOps
Prior work with GenAI technologies: RAG systems, AI agents, or LLM-based applications
8+ years of Python experience
Hands-on experience with AI coding assistants (Cursor, GitHub Copilot, Claude Code)
3+ years of NodeJS, Java, Rust, C++, or Go experience
Tech stacks you will learn with
LLM Platforms
OpenAI
Anthropic Claude
Google Gemini
Meta Llama
Vector Databases
Weaviate
Pinecone
Qdrant
ChromaDB
Development Tools
Python
FastAPI
Git
Docker
Airflow
Pytest
Evaluation & Monitoring
Ragas
LangSmith
Weights & Biases
Grafana
Prometheus
Frameworks
LangChain
LlamaIndex
HuggingFace
PyTorch
TensorFlow
Cloud & MLOps
AWS SageMaker
AWS Bedrock
GCP Vertex AI
Docker
Kubernetes
Week-by-week course content
AI Leadership
Weeks 1
Sharpen your leadership skills to deliver measurable ROI impact with LLMs
Frameworks for driving strategy, impact, and investment decisions
The AI scaling laws and why they matter for business
AI architecture from a commercial perspective
Cross-functional decision making
LLM Engineering Foundations
Weeks 2-3
Understand transformers and build your first Gen AI products.
Neural networks to modern LLM architectures
Embeddings, tokenization, attention mechanisms
Frontier vs open-source models (GPT, Claude, Gemini, LLaMA)
Chat Completions API and multi-model orchestration
Build

AI-powered brochure generator and multi-modal customer support agent.

Agentic AI Foundations
Weeks 4-5
Master autonomous AI agents with leading frameworks.
Agent vs workflow patterns, LLM autonomy
OpenAI Agents SDK, tool integration, function calling
CrewAI, LangGraph, and AutoGen frameworks
Multi-agent collaboration and deep research patterns
Build

Career Digital Twin, SDR Agent, and 4-Agent Engineering Team.

Production AI & Fine-Tuning
Weeks 6-7
Master RAG, fine-tuning, and MCP for production systems.
Vector embeddings and semantic search
RAG architectures with LangChain
QLoRA fine-tuning of open-source models
Model Context Protocol (MCP) servers and tools
Build

RAG knowledge worker and Trading Floor with 6 MCP servers.

MLOps & Cloud Deployment
Week 8-9
Deploy production AI to AWS, GCP, and Azure.
Full-stack AI with Next.js, FastAPI, Docker
AWS: Lambda, Bedrock, API Gateway, S3, CloudFront
Terraform infrastructure-as-code
GitHub Actions CI/CD pipelines
Build

Multi-Agent systems and Agentic Loops

Capstone Project
Week 10
Build a complete, production-grade AI system.
Multi-agent architecture with Aurora Serverless, Lambda, SQS
JWT authentication and CloudFront frontends
LangFuse observability and monitoring
Security guardrails and responsible AI
Deliver

Portfolio-worthy project demonstrating enterprise AI skills.

Apply to AI Academy

Ready to Accelerate Your AI Career?

Join an elite cohort of 150 engineers transforming the future of technology. Applications are competitive. Take our assessment to apply.

Apply to AI Academy
Profile card of Samantha C., Senior Data Analyst from Brazil, GMT+2 timezone, 4 hours overlap, with a monthly rate of $5,000 to $6,000.Profile card of Samantha C., Senior Data Analyst from Brazil with GMT+2 timezone and 4 hours overlap, salary range $5,000 to $6,000 per month.

Subscribe for insights on building and scaling AI systems.

Decorative graphic element
Field required
Thank you, we received your contact information!
Choose your program
Kubernetes
Apply now
AI Engineering Curriculum
Apply now