Team upskilling program for minerals processing professionals

Get more value from your operation

Interlate’s Practical Data Analytics program is designed to share practical insight and transfer capability in data analytics and machine learning for the mining and minerals processing sector. Designed and delivered by Interlate’s Process Engineer / Data Scientists, the program uses real world examples and hands-on access to Interlate’s analytical application www.clarofy.ai

We use proprietary capability building programme (4 modules delivered over 12 hours) and software www.clarofy.ai to support and strengthen site-based data science literacy.

Learn how to use data to identify plant parameter ranges of best past performance for your different feed types, quantify productivity improvement as well as the all-important operation tactics secure the benefits going forward.

Course Overview

Module 1: Agile methodology for Data Science projects – 2 hours

Improve adaptability of teams and ROI of Data Analytics projects by utilising the basic concepts of Agile methodology

Module 2: Data Science workflow – 3 hours

An overview of the data analytics process, understand the steps involved and how to communicate it with stakeholders.

Module 3: Practical Problem Solving to Data Analytics – 4 hours

How practical data analytics can be applied to deliver value and traps to avoid.

Module 4: Machine Learning Modelling – 3 hours

Basic understanding of when and how to apply machine learning modelling. Understand the process involved, including inputs and decisions necessary.

Who should attend?

• Plant Engineers, Data Scientists and Operators

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