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Technical Training

Build the In-House Capability to Own Your Data

We don't just build solutions — we transfer the knowledge so your team can maintain, extend, and build on what we create together.

Practical training that builds real capability — not just certificates

Most organisations rely on external consultants for capabilities that should live in-house. We believe the best outcome of any engagement is a client team that can eventually do it themselves. That's why knowledge transfer is built into everything we do.

Our training programmes are designed for engineers, process technicians, analysts, and IT professionals who work in industrial environments. We use your data, your systems, and your business problems as the learning material — so every session is immediately relevant and practically applicable. Courses are delivered on-site, remotely, or in a blended format, and can be tailored to the exact skill level and role of your team.

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Data Science Fundamentals

Statistics, probability, data cleaning, exploratory analysis, and visualisation — the foundations every data practitioner needs to be effective.

Machine Learning Practical

Hands-on machine learning using Scikit-learn and TensorFlow — covering regression, classification, clustering, and neural networks with real datasets.

Data Engineering Workshops

Pipeline design, ETL development, database management, and cloud data infrastructure — practical skills for building and maintaining data systems.

Analytics Tools Training

Structured training in Power BI, Python for analytics, SQL, and Jupyter notebooks — delivered at the pace and depth your team needs.

Courses designed for industrial and technical professionals

Every course uses real industrial data and scenarios — making the learning immediately transferable to your day-to-day work.

Python for Data Science

From Python basics through to data manipulation with Pandas, numerical computing with NumPy, and visualisation with Matplotlib and Seaborn.

Machine Learning with Scikit-learn & TensorFlow

Practical ML covering supervised and unsupervised learning, model evaluation, and deployment — using datasets from mining and manufacturing environments.

Data Pipeline Design

End-to-end pipeline architecture using Apache Airflow and dbt — covering ingestion, transformation, validation, and delivery to analytics systems.

SQL & Database Fundamentals

Structured Query Language from foundational queries through to advanced analytics functions, window functions, and performance optimisation.

Power BI & Dashboard Design

Data modelling in Power BI, DAX fundamentals, visual best practices, and report publishing — from first dashboard to enterprise-grade BI solution.

PLC & Industrial Data Basics

An introduction to PLC data structures, industrial protocols (OPC-UA, ModBus), historian systems, and how to access and use OT data for analytics.

Built for people who learn by doing

01

Hands-On Learning

Every session is built around exercises, projects, and real data — not slides. Participants leave with working code, built pipelines, and practical skills they can use from day one.

02

Industry-Specific Context

All examples, datasets, and case studies are drawn from mining, manufacturing, and industrial environments — so the learning always connects directly to your team's real challenges.

03

Custom Curriculum

We don't run off-the-shelf courses. Every programme is scoped to your team's current skill level, learning objectives, and the specific tools and systems they work with every day.

Invest in Your Team's Data Capability

Tell us about your team's current skill level and what you want them to be able to do — and we'll design a programme that gets them there.