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Advanced Professional Certificate in Machine Learning in Mining

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Advanced Professional Certificate in Machine Learning in Mining

  • Instructor AFIMPP
  • Category Machine Learning
The Course Curriculam

COURSE CODE – MLM 111
Fundamentals of Machine Learning Participants delve into the fundamental principles of machine learning, including supervised learning, unsupervised learning, reinforcement learning, and deep learning. They learn about different machine learning algorithms, optimization techniques, and evaluation metrics.

  • Machine Learning Fundamentals
  • Fundamentals

COURSE CODE – MLM 112
Data Pre-processing and Feature Engineering focuses on data pre-processing techniques and feature engineering methods specific to mining applications. Participants learn how to clean, transform, and pre-process raw mining data to prepare it for machine learning algorithms. They also explore methods for extracting informative features from mining datasets.

COURSE CODE – MLM 113
Predictive Modelling in Mining Participants study advanced predictive modelling techniques used in mining applications, such as regression analysis, classification algorithms, time series forecasting, and anomaly detection. They learn how to build predictive models to optimize mining processes, improve resource estimation, and predict equipment failures.

COURSE CODE – MLM 114
Optimization and Control with Machine Learning Participants explore how machine learning techniques can be applied to optimize and control various aspects of mining operations, including production scheduling, equipment optimization, process control, and energy management. They learn about optimization algorithms, reinforcement learning approaches, and control theory principles.

COURSE CODE – MLM 115
Remote Sensing and Image Analysis Machine learning plays a crucial role in analysing remote sensing data and images acquired from satellites, drones, or other aerial platforms in mining applications. Participants learn about image processing techniques, object detection algorithms, and classification methods for extracting useful information from remote sensing data.

COURSE CODE – MLM 116
Geological Data Analysis Participants gain expertise in analysing geological data using machine learning techniques. They learn how to integrate geological data with other types of mining data, such as drill hole data, geochemical data, and geophysical data, to gain insights into mineral exploration, resource characterization, and geological mapping.

COURSE CODE – MLM 117
Big Data Analytics and Cloud Computing Participants explore techniques for handling large-scale mining datasets, including distributed computing, parallel processing, and cloud-based data analytics platforms. They learn how to leverage big data technologies to analyse massive volumes of mining data efficiently.

COURSE CODE – MLM 118
Case Studies and Practical Applications The program may include case studies, projects, and hands-on exercises that apply machine learning techniques to real-world mining datasets and problems. Participants gain practical experience in data analysis, model development, and interpretation of results in mining contexts.

COURSE CODE – MLM 119
Ethical and Regulatory Considerations Participants learn about ethical considerations and regulatory requirements related to the use of machine learning in mining applications. They explore issues such as data privacy, algorithmic bias, and transparency in machine learning models.

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AFIMPP

25 Courses 14 Students
5.0
Total 3 Ratings
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  • A

    Anonymous

    9 months ago
    This was my first time taking an online course. The content is excellent, and the instructors are also excellent. How much you learn from this course is pretty much what you put intto it.
  • A

    Anonymous

    5 years ago
    This was my first time taking an online course. The content is excellent, and the instructors are also excellent. How much you learn from this course is pretty much what you put into it.
  • A

    Anonymous

    5 years ago
    Thank you! I enjoyed your course and humor. Please keep working on making great stuff to share and help more people. Look forward to more additional features to this project near future.

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