Data Analytics for Asset Care
$950.00
Class 1: Data Collection and Cleaning
• Data sources and types (sensor data, historical data, operational data)
• Data collection methods and systems
• Data quality assessment and cleaning
• Data preprocessing techniques (normalization, standardization, outlier detection)
Class 2: Statistical Analysis and Data Visualization
• Descriptive statistics (mean, median, mode, standard deviation)
• Exploratory data analysis (EDA)
• Data visualization techniques (charts, graphs, dashboards)
• Hypothesis testing and statistical inference
Class 3: Machine Learning Applications in Asset Care
• Introduction to machine learning
• Supervised learning (regression, classification)
• Unsupervised learning (clustering, dimensionality reduction)
• Deep learning techniques (neural networks)
• Machine learning model evaluation and selection
Class 4: Predictive Modeling and Anomaly Detection
• Time series analysis and forecasting
• Predictive maintenance models
• Anomaly detection techniques (statistical methods, machine learning)
• Model deployment and monitoring
Class 5: Data-Driven Decision-Making
• Data-driven asset management strategies
• Decision support systems
• Key performance indicators (KPIs) and metrics
• Return on investment (ROI) analysis
• Continuous improvement and optimization
