Global Certificate in Mining Data Solutions

• Data Mining Fundamentals: Introduction to data mining, data types, and sources. Understanding data pre-processing, data quality, and data warehousing.
• Statistical Analysis and Data Mining: Basic statistical concepts, data visualization, and exploratory data analysis. Hypothesis testing, regression analysis, and correlation.
• Machine Learning Techniques in Mining: Supervised and unsupervised learning, decision trees, random forests, and ensemble methods. Neural networks, deep learning, and reinforcement learning.
• Data Mining Tools and Software: Overview of popular data mining tools, including Weka, RapidMiner, KNIME, and Python libraries. Hands-on experience with data mining software.
• Big Data and Mining Technologies: Introduction to Hadoop, Spark, and NoSQL databases. Data processing and analysis in distributed environments.
• Data Mining Applications in Mining Industry: Real-world examples of data mining applications in the mining industry, including mineral exploration, mine planning, and operations optimization.
• Ethics and Regulations in Mining Data Solutions: Data privacy, security, and ethical considerations. Legal and regulatory requirements for data handling and storage.
• Data Mining Project Management: Project planning, execution, and monitoring. Managing data mining teams and stakeholders.