Ocean state estimation requires expertise in diverse subjects including estimation theory, numerical modeling, and observational oceanography. The individual subject matters are often treated separately, often leading to misunderstandings about model-data synthesis. The Summer School will examine these subjects in a coherent manner for the students to gain a working understanding of ocean state estimation and its use in ocean research. Topics under estimation will include inverse theory, optimization, Kalman filtering and related smoothing, adjoint method, and algorithmic differentiation (AD) tools. Principles of numerical modeling will be described using the MITgcm as an example. Advanced modeling algorithms and concepts, especially those employed in the ECCO Central Estimate, will be treated including mixing schemes, coordinate systems, and boundary conditions. Practical issues will be discussed such as the basics of model parallelization and the nature of model errors. Different observing systems will be described, focusing on their complementary nature and impact on state estimation. Sources of data error will be examined and issues of data reduction will be discussed. A range of analysis tools developed within the ECCO consortium will be introduced through tutorials and projects.