Software reverse engineering skills are fundamental to producing a capable cyber security workforce. However, analyzing binaries is often difficult for computer science students and others in related areas due to the curriculum emphasis on efficient software development. At the same time, while artificial intelligence techniques, powered by machine learning and deep learning models, have shown promise to make software reverse engineering less labor intensive, there are a number of practical challenges software reverse engineers must overcome so that they are practically effective for program analysis and software reverse engineering. In this presentation, we will summarize our efforts in incorporating AI techniques to our software reverse engineering courses, where IDA Pro and Ghidra are used as the main tools. With proper setups, we show that the tools for control flow and data flow techniques along symbolic executions can be effective in malware analysis.