Here are some types of project objectives that students can achieve using R to analyze data, visualize the analysis using a Shiny app, and build the application for non-expert users. Students will also employ statistical and machine learning methods:

Predictive Modeling Project:

• Objective: Build a Shiny app that predicts a target variable using machine learning algorithms. Provide a user-friendly interface for non-expert users to input data and receive predictions.

Exploratory Data Analysis (EDA) Dashboard:

• Objective: Develop a Shiny app that allows users to explore and understand the dataset visually. Include interactive plots and summary statistics to assist non-expert users in grasping key insights.

Cluster Analysis Visualization:

• Objective: Implement a Shiny app that performs cluster analysis on a dataset and visualizes the clusters using interactive plots. Enable users to intuitively interpret the grouping patterns.

Time Series Forecasting App:

• Objective: Create a Shiny app that utilizes time series data to make predictions. Include options for users to adjust forecasting parameters and visualize the predicted values over time.

Feature Importance Explorer:

• Objective: Build a Shiny app that applies machine learning models to identify and visualize feature importance in a dataset. Simplify the interpretation for non-expert users.

Interactive Machine Learning Comparison:

• Objective: Develop a Shiny app that allows users to compare the performance of different machine learning algorithms on a given dataset. Provide a user-friendly interface for model selection.

Anomaly Detection System:

• Objective: Construct a Shiny app that employs statistical methods or machine learning to detect anomalies in a dataset. Design the application to present identified anomalies in a clear and understandable manner.

Dynamic Data Filtering Tool:

• Objective: Create a Shiny app that enables users to dynamically filter and explore data based on different criteria. Ensure a user-friendly interface for non-expert users to navigate through the dataset.

Prediction Explanation Interface:

• Objective: Develop a Shiny app that not only makes predictions but also provides explanations for the predictions. Use techniques such as SHAP (SHapley Additive exPlanations) to enhance interpretability.

Interactive Data Summary Dashboard:

• Objective: Design a Shiny app that generates interactive and informative summaries of key statistics and insights from a dataset. Ensure the summaries are presented in a way that is accessible to non-expert users.