Signal processing algorithms and DSP chips are embedded nearly in every application that involves natural signal or data analysis and/or synthesis. Applications of digital signal processing (DSP) in engineering include electrical, mechanical, chemical, industrial and biomedical systems. Applications in other areas include entertainment, financial, health, computing, manufacturing, to name a few. At ASU we developed an elective course for an undergraduate program called Digital Culture that includes gaming, smart stages, computer music, visualization and other applications. We have offered the course online to arts majors in 2013. We begun adding multidisciplinary application content to this course and offered it again in 2015 as a hybrid online course with compulsory weekly on-campus sessions. Arrangements are being made to include it as an elective course in information management systems, computer informatics, mechanical engineering, and biomedical informatics. The course now includes several introductory topics in signal processing covered mostly at a qualitative and block diagram level; we added several simulations in MATLAB and in Java-DSP. The course covers basics of DSP starting from time and frequency domain analysis and sampling. It then covers digital FIR ad IIR filters and the FFT. About one third of the course covers applications which introduce qualitative descriptions of some advanced topics. For example, linear prediction and coding of speech are described at the block diagram level with MATLAB and Java simulations. Extensions to 2-D signal processing are covered as well with the focus on JPEG and MPEG applications. The syllabus, simulations and preliminary assessments of this course are presented in the paper.