The teaching reform of law courses is to further enhance the development speed of the law education business. In this paper, a practical teaching platform for law courses is constructed based on Internet technology, and context-aware class case matching is performed by using word embedding of the BERT network and contextual information extraction of the Bi-LSTM model. Then the local semantic feature extraction by CNN network and collaborative filtering algorithm based on user preferences are used to achieve intelligent recommendation analysis of law course cases, and experimental simulation analysis is conducted for the teaching platform and recommendation algorithm. In terms of platform performance, the average response time is 24.5ms, which is 12.67% and 26.99% less than that of the Mucuo platform and Tencent Classroom, respectively. From the recommendation algorithm, the accuracy of recommendation based on students’ preferences is 68%. This shows that the practical teaching platform of law courses can be the implementation path of law teaching reform in the Internet era.