AI / ML Engineer Roadmap
Go from Python basics to building and deploying real machine-learning and AI agent systems.
A practical AI engineering path focused on shipping, not just theory. You move from programming and data through classic machine learning, deep learning and modern LLM applications, finishing with how to deploy and operate AI in production the way NUEXUS does for clients.
By the end, you will be able to
- Build, train and evaluate machine-learning models
- Work with deep learning and modern LLMs
- Build retrieval-augmented and agentic AI applications
- Deploy and monitor AI systems responsibly in production
Your step-by-step path
Follow the stages in order. Each one builds on the last, from fundamentals to job-ready.
Python & Data Foundations
The toolkit every AI engineer builds on.
Machine Learning Core
Understand how models actually learn and how to judge them.
Deep Learning
Step up to neural networks and modern architectures.
LLMs & Generative AI
Build with the models reshaping the industry.
MLOps & Deployment
Get models out of the notebook and into production.
Job-Ready: AI Engineer
Ship an end-to-end project and learn to do it responsibly.
Certifications you can target
We prepare you for recognized industry certifications and award a verifiable NUEXUS credential at the end of the path.
- Cloud AI/ML certifications
- Deep-learning specializations
- NUEXUS Certified AI Engineer
Trainings that power this path
Each stage maps to NUEXUS trainings, delivered live online, in classroom or at your site.
Frequently Asked Questions
Explore other paths
Build it right.
Secure it for good.
Tell us what you're building or securing. We'll bring the engineers, the security team and the trainers, plus a clear, costed plan to get you there.
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