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AI+ Mining Practitioner™

Course code: NPAP2011

Formerly known as AI+ Mining™

Unlock the potential of AI in Mining to optimize exploration, improve resource management, and automate operations.

  • Powering the Next Era of Mining with AI: Smarter, Safer, and Sustainable Operations
  • Beginner-Friendly Course: Perfect introduction to explore how AI transforms modern mining practices
  • Foundational Learning: Explains AI-driven exploration, automation, data analysis, and safety innovations
  • No Technical Background Needed: Open to anyone eager to understand the role of technology in mining
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI for Resource Exploration

Learn how AI can optimize the discovery and analysis of mineral deposits through geospatial data and predictive models.

Predictive Maintenance

Gain expertise in using AI to predict equipment failures and reduce downtime, ensuring smoother mining operations.

Smart Mining Automation

Understand how AI technologies enable automation in mining, improving operational efficiency and safety.

Environmental Impact Analysis

Learn to use AI for monitoring and reducing the environmental impact of mining activities, enhancing sustainability.

Data-Driven Decision Making

Develop skills to analyze large datasets from mining operations, using AI to improve resource management and operational strategies.

Course structure

Module 1: Introduction to AI in Mining

  • 1.1 Overview of AI, ML & Deep Learning in Mining
  • 1.2 Use Cases
  • 1.3 Activity

Module 2: Machine Learning & Deep Learning for Mining

  • 2.1 Introduction to ML & Deep Learning
  • 2.2 Use Cases
  • 2.3 Case Study
  • 2.4 Hands-On Exercise
  • 2.5 Activity

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

Module 4: AI for Equipment Automation & Fleet Optimization

  • 4.1 AI in Autonomous Vehicles & Robotics
  • 4.2 Use Cases
  • 4.3 Case Study
  • 4.4 Hands-On Exercise
  • 4.5 Activity

Module 5: AI in Predictive Maintenance & Asset Management

  • 5.1 AI in Equipment Health Monitoring
  • 5.2 Use Cases
  • 5.3 Case Study
  • 5.4 Hands-On Exercise
  • 5.5 Activity

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
  • 8.3 Case Study

Prerequisites

  • 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
  • Recommended: Prior exposure to GIS, geospatial data, or industrial automation is a plus but not mandatory

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