Industry Specialisations · Self-paced
AI+ Mining™
Apply AI to Drive Safer, Smarter, and More Efficient Mining Operations.
Executive summary
The AI+ Mining course explores how artificial intelligence is transforming the mining industry. It covers AI fundamentals, machine learning, and deep learning applications in exploration, operations, predictive maintenance, and workforce development. The course emphasizes ethical AI, regulatory compliance, and AI-powered AR/VR training for workforce upskilling. It also highlights strategic decision-making, risk management, and supply chain optimization. Real-world case studies from leaders like Vale and Anglo- American illustrate practical AI benefits. This course prepares mining professionals to harness AI for safer, more efficient, and sustainable mining operations in today’s competitive landscape.
Built for these roles
Before you start
Basic understanding of mining industry operations and terminology
Familiarity with fundamental concepts of data analytics and statistics
No prior coding experience required (coding templates provided)
Prior exposure to GIS, geospatial data, or industrial automation is a plus but not mandatory
One-time price
$110
8 hours, self-paced. Lifetime access, certificate included.
Certification exam included (limited attempts).
Secure checkout via Stripe. Instant access after payment.
Curriculum
What you'll cover.
8 hours of self-paced content. Work through it in order, on your schedule.
Module 1: Introduction to AI in Mining
1.1 Overview of AI, ML & Deep Learning in Mining
1.2 Use Cases
1.3 Activity: Group Discussion – How is AI changing the mining industry
Module 2: Machine Learning & Deep Learning for Mining
2.1 Introduction to ML & Deep Learning
2.2 Use Cases
2.4 Case Study: AI-Powered Geophysical Analysis
2.5 Hands-On Exercise
2.6 Activity: Group Discussion – Will AI Replace Traditional Geologists and Mining Engineers
Module 3: AI in Mineral Exploration & Resource Modeling
3.1 AI for Smart Exploration & Orebody Modeling
3.2 Use-Cases
3.3 Case Study
3.4 Hands-On Exercises
3.5 Activity: Group Discussion – Present an AI-powered Exploration Plan to a Mining Board Collaborate to
Module 4: AI for Equipment Automation & Fleet Optimization
4.1 AI in Autonomous Vehicles & Robotics
4.2 Use Cases
4.2 Case Study
4.5 Activity: Group Discussion:"Is mining ready for full automation
Module 5: AI in Predictive Maintenance & Asset Management
5.1 AI in Equipment Health Monitoring
5.2 Use Cases
5.3 Case Study: AI in Predictive Equipment Failure – Reducing Unplanned Downtime in Mining
5.4 Hands-On Exercise: AI for Equipment Monitoring – AI-Powered Sensor Data Analysis Using
5.6 Activity: Group Discussion - "Should AI Decide When Machines Need Maintenance?"
Module 6: AI for Environmental Compliance & Sustainability
6.1 AI-Powered Environmental Monitoring
6.2 Use Cases
6.3 Case Study
6.4 Hands-On Exercises
6.5 Activity: Group Exercise
Module 7: AI for Workforce Transformation & Ethical AI
7.1 Ethical AI, Workforce Augmentation & AI Regulations
7.2 Use Cases
7.3 Case Study
7.4 Hands-On Exercises
Module 8: AI in Mining Strategy & Implementation
8.1 AI-Driven Decision-Making in Mining
8.2 Use Cases: Explore AI applications in supply chain optimization and commodity price forecasting.
8.3 Case Study: Vale’s AI-Driven Supply Chain Optimization Strategy
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