Advanced Analytics with RapidMiner Training Course

Introduction

• Overview of RapidMiner Studio for government
• Orientation to the RapidMiner user interface and features

CRISP-DM Methodology in RapidMiner

• Understanding the CRISP-DM framework for government data projects
• Application in estimation and projection of values within public sector contexts

Data Understanding and Preparation

• Data import and exploration techniques for government datasets
• Preprocessing and cleaning methods tailored to government data
• Advanced data transformation methods for enhanced analysis

Data Modeling with RapidMiner

• Introduction to data modeling for government applications
• Selection and application of machine learning algorithms suitable for public sector use
• Supervised learning algorithms for predictive analytics in government
• Unsupervised learning algorithms for pattern recognition in government datasets

Model Evaluation and Deployment

• Techniques for model evaluation to ensure accuracy and reliability in government projects
• Strategies for model deployment within public sector workflows
• Model realignment and optimization to maintain performance over time

Time Series Analysis and Forecasting

• Fundamentals of time series analysis for government data
• Application of moving average models in public sector forecasting
• Time series preprocessing and data aggregation techniques for government datasets

Advanced Time Series Techniques

• Decomposition analysis to understand underlying trends in government data
• Projection with time windows for accurate forecasting in the public sector
• Projection with feature generation to enhance predictive models

ARIMA Modeling

• Understanding ARIMA models for government data analysis
• Practical application of ARIMA models in RapidMiner for government projects

Summary and Next Steps