Copperhead is a data parallel language embedded in Python, which aims to provide both a productive programming environment as well as excellent computational efficiency on heterogeneous parallel hardware. Copperhead programs are written in a small, restricted subset of Python, using standard constructs like map and reduce, along with traditional data parallel primitives like scan and sort. Copperhead programs are written in standard Python modules and interoperate with existing Python numerical and visualization libraries such as NumPy, SciPy, and Matplotlib. The Copperhead runtime compiles Copperhead programs to target either CUDA-enabled GPUs or multicore CPUs using OpenMP or Threading Building Blocks. On several example applications from Computer Vision and Machine Learning, Copperhead programs achieve between 45-100% of the performance of hand-coded CUDA code, running on NVIDIA GPUs. In this talk, we will discuss the subset of Python that forms the Copperhead language, the open source Copperhead runtime and compiler, and selected example programs.