<p>This study discusses the application of deep reinforcement learning in the design and optimization of English continuing education teaching content. Aiming at the one-size-fits-all problem in the traditional education model, it puts forward personalized teaching strategies based on deep reinforcement learning. Analyze the real-time feedback of students’ learning behavior, automatically adjust the teaching content, and provide learning paths suitable for students’ needs. A deep reinforcement learning model is constructed, and the effectiveness of this method in improving students’ learning effect and teaching efficiency is verified by combining data collection, p reprocessing, model training and evaluation. Deep reinforcement learning model can effectively enhance students’ learning participation and improve learning results. Data quality, computing resource consumption and super-parameter tuning have important effects on model performance. With the development of deep reinforcement learning technology, personalized education mode will be applied in more educational scenes to promote the intelligent and personalized development of education.</p>