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
Who should attend?
Plant Engineers, Data Scientists and Operators
Module 1: 2 HoursAgile methodology for Data Science projects
Improve adaptability of teams and ROI of Data Analytics projects by utilising the basic concepts of Agile methodology
Module 2: 3 HoursData Science workflow
Improve adaptability of teams and ROI of Data Analytics projects by utilising the basic concepts of Agile methodology
Module 3: 4 HoursPractical Problem Solving to Data Analytics
How practical data analytics can be applied to deliver value and traps to avoid.
Module 4: 3 HoursMachine Learning Modelling
Basic understanding of when and how to apply machine learning modelling. Understand the process involved, including inputs and decisions necessary.
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Do you want to help create a more sustainable future?
If you are the type of person that is driven to create a better future by using science, technology and teamwork, Interlate might be a good fit for you.