The book "Parameter Estimation in Stochastic Differential Equations" offers a comprehensive analysis of estimating unknown parameters in stochastic differential equations and stochastic partial differential equations. It is aimed at researchers and practitioners from various fields of mathematics as well as related disciplines such as economics and finance. The content includes both continuous and discrete observations and thoroughly discusses methods such as maximum likelihood, minimum contrast, and Bayesian approaches. Particularly relevant is the investigation of the asymptotic properties of multiple estimators, especially in the context of large observation periods and small time intervals. Additionally, it covers models driven by spatio-temporal white noise, as well as more complex non-Markovian and non-semimartingale models like fractional diffusion, which model long-term memory phenomena. These aspects make the book a valuable resource for the analysis of complex phenomena.