Learn by Doing. Solve Problems with Machine Learning.

At ML Skills Academy, we help businesses build workforce-ready machine learning teams through project-based learning that mirrors real-world ML workflows.

Our hands-on approach ensures teams develop practical, industry-relevant skills—without disrupting operations or compromising security.

20.03.24                          
Cleidi Hearn, TUS New Frontiers. Picture: Alan Place.

Machine learning is more than a skill—it’s a competitive advantage.

We redefine ML training with industry tailored, disruption-free ML projects that let your teams learn, collaborate, and apply skills without impacting operations.

Our Vision

We envision a future where businesses seamlessly integrate machine learning into their operations, driven by teams that are confident, skilled, and ready to deliver impactful solutions.

Our Mission

To bridge the gap between theory and practice, helping businesses develop skilled teams capable of solving complex problems and driving innovation through machine learning.

Our Approach

We believe the best learning happens by doing. Our hands-on, project-based training immerses teams in real-world, industry-specific machine learning projects, covering the entire ML lifecycle—from data preparation to deployment. Designed to simulate workplace dynamics, each project fosters collaboration and is fully tailored to your business goals.

WHAT MAKE US DIFFERENT

Machine Learning Upskilling That Works.

Project-Based Learning

We don’t teach courses; we solve problems. Teams learn by completing industry-specific ML projects that reflect real-world challenges.

Practical Results, Not Theory

Our training delivers hands-on experience with measurable outcomes, preparing your workforce to implement ML solutions immediately.

Industry Relevance

Every project is tailored to your sector’s needs, ensuring teams build skills directly applicable to their roles and business goals.

Collaborative Learning

We replicate workplace dynamics, enabling teams to develop the skills and workflows needed for seamless collaboration on ML projects.