Advances in AI and large language models have transformed fields like natural language processing and coding. These changes bring both opportunities and challenges for computer education. While these powerful tools can enhance teaching and personalize learning, they also raise concerns about over-reliance and academic honesty. This paper presents practical ways to use big models effectively in computer education while managing potential risks. We focus on three key areas: (1) customized learning with AI assistance, (2) smart teaching tools, and (3) combining different subjects. Our approach helps students learn better while developing strong computational thinking skills.