This paper presents a newly developed course for teaching parallel programming to undergraduates. This course uses a flipped classroom model and a "hands-on" approach to learning with multiple real-world examples from a wide range of science and engineering problems. The intention of this course is to prepare students from a variety of STEM backgrounds to be able to take on supportive roles in research labs while they are still undergraduates. To this end, students are taught common programming

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... paradigms such as benchmarking, shared memory parallelization (OpenMP), accelerators (CUDA), and shared network parallelization (MPI). Students are also trained in practical skills including the Linux command line, workflow/file management, installing software, discovering and using shared module systems (LDMOD), and effectively submitting and monitoring jobs using a scheduler (SLURM).