In the digital era, Classical Music plays a dominant role in our daily lives. It often concurs in commercials, games, movies, and more. In general, Classical Music falls between the Baroque, Classical, Romantic, and Modernist eras. Among all these different musical periods, musicians nowadays might be proficient only to a number of them. With the AI, composers, musicians, or even non-specialists without Classical Music backgrounds could quickly get on to their journey in Classical Music composition. Recently, AI music composition has become more popular and accessible to people. However, most AI music generator platforms only focus on creating modern Music. Moreover, they usually categorize all genres of Classical Music into a single category – Classical Music. Since most research in this field adopted LSTMs to generate Music, it is worthwhile to discover different types of machine learning methods such as CNN-GANs for this task. Perhaps the proposed models could set successful precedence in this research area. This project aims to generate Classical Music using generative models – Bi-LSTM and CNN-GAN to compose Classical Music for four Classical Music genres and evaluate their performance respectively and collectively. Also, to further explore and strengthen the area of AI in music composition.