Another way to handle OOP exceptions and errors is to use logging and debugging tools, which allow you to record and inspect the events and states of your program. Logging is useful for tracking the progress and performance of your AI and ML scenarios, as well as identifying any errors or anomalies. You can use the logging module in Python to configure different levels of logging, such as debug, info, warning, error, or critical. Debugging is useful for finding and fixing the root causes of your errors, as well as testing and verifying your code. You can use the pdb module in Python to set breakpoints, examine variables, execute commands, or step through your code.