Training on Data Mining and Analysis

Module 1: Fundamentals of Data Mining and Analysis

• Overview of data mining processes, techniques, and applications
• Key steps in transforming data into insights
• Introduction to data mining tools and workflows
• Case Study: Identifying business patterns from customer transaction data
• Practical: Analyze a dataset to uncover basic trends and patterns

Module 2: Data Preparation and Exploration

• Data cleaning, handling missing values, and transformation methods
• Exploratory data analysis and visualization fundamentals
• Data profiling and summary statistics
• Case Study: Preparing and visualizing development survey datasets
• Practical: Clean and explore a dataset using basic EDA techniques

Module 3: Classification and Prediction Techniques

• Logistic regression, decision trees, and supervised learning models
• Evaluating model accuracy and predictive performance
• Model validation and interpretation
• Case Study: Predicting credit risk or project success outcomes
• Practical: Build and evaluate a simple predictive model

Module 4: Clustering and Association Analysis

• Unsupervised learning: K-means and hierarchical clustering
• Association rule mining for identifying hidden relationships
• Interpreting clustering and association results
• Case Study: Segmenting program beneficiaries for targeted interventions
• Practical: Perform clustering and association analysis on sample data

Module 5: Data Visualization and Reporting

• Building interactive dashboards and analytical reports
• Presenting patterns, trends, and insights for strategic decisions
• Data storytelling and visualization best practices
• Case Study: Developing a visual performance dashboard for management
• Practical: Create a dashboard and present insights from analyzed data