This chapter provides a hands-on programming tutorial for advanced DEA models, designed to bridge theoretical concepts with practical application. It systematically guides readers through the implementation of several key models, beginning with the foundational slack-based measure (SBM). The tutorial then extends this framework to incorporate undesirable outputs (e.g., emissions), a critical consideration for robust environmental efficiency analysis. Further detail is provided on programming both the directional distance function (DDF) and its more flexible variant, the non-radial DDF. Shifting from static to dynamic performance measurement, the chapter elucidates the computational steps for the Malmquist productivity index (MPI) to track productivity changes over time. Finally, it culminates in programming the Malmquist-Luenberger (ML) productivity index, which integrates undesirable outputs into a dynamic framework, offering a powerful tool for assessing green productivity growth. This practical guide equips researchers and analysts with the necessary coding skills to apply a comprehensive suite of modern DEA techniques.