Step 1: Demo Section

In the demo section, there are five example problems. Each problem is associated with a specific Bayesian Network that visually represents the relationships between various variables.

Step 2: Example Problems and Solutions

For each example problem, a Bayesian Network is provided. Click on Show Solution next to the given question to see detailed steps on how to calculate the solution. This feature demonstrates the process of solving questions in different domains, offering a thorough understanding of the methodology.

Step 3: Study the Bayesian Networks and Solutions

Examine the Bayesian Network provided for each example to understand the connections between variables. The solutions detail how to use these connections and the Conditional Probability Tables (CPTs) to calculate the required probabilities.

Step 4: Practice Section

After learning from the examples in the demo section, go to the practice section where a new set of domain problems are given. These problems are designed for you to apply the knowledge and techniques you've learned from the theory and demo.

Step 5: Apply Your Knowledge

In the practice section, you'll use the Bayesian Networks to calculate the probabilities for each question. Click on nodes to view their CPTs, and apply the formula mentioned in the theory to find your solutions.

Step 6: Refer to the Hints Section if Needed

If you find the practice problems challenging, the hints section provides guidance. This includes a solved iteration of the algorithm, demonstrating how to apply the theoretical concepts to compute the probabilities in the Bayesian Network.

Step 7: Check Your Answers

Complete the practice problems and then click the Check button to submit your answers.