IT Infrastructure
Network & Systems Engineer Track
Build the backbone of modern IT. Networking, Windows Server, Linux administration and virtualisation with hands-on lab environments.
Data & Analytics
AI & Machine Learning Engineer Track
Move into one of tech's fastest-growing roles. Python, machine learning, LLM applications and MLOps with production-focused projects.
What you will learn
- Build and evaluate machine learning models with scikit-learn and PyTorch
- Develop applications on top of large language models
- Deploy models to production with MLOps best practice
- Work with real datasets end to end
- Ship an AI capstone employers can test-drive
About this course
Move into one of tech’s fastest-growing roles. Python, machine learning, LLM applications and MLOps with production-focused projects.
Syllabus
01 Python & Maths Refresher
NumPy, pandas and the maths that matters.
02 Classical Machine Learning
Regression, classification and evaluation.
03 Deep Learning
Neural networks and PyTorch.
04 LLMs & Applied AI
Prompting, retrieval and building AI products.
05 MLOps
Serving, monitoring and iterating on models.
06 Capstone & Career Sprint
Production AI project, portfolio and interviews.
Your lead instructor
Dr. Eimear Brady
ML Engineer, PhD, previously applied-AI lead at a global consultancy
14-day satisfaction guarantee
If the course is not right for you, tell us within the first 14 days for a full refund — no questions asked.
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