In recent years, data science has revolutionized how we make sense and extract information from data. With recent advancements in neuroscience and availability of data, large amounts of data are available for scientists to analyze. In this course we aim to provide data science tools for the challenges encountered in neuroscience datasets, including noise, high dimensions, and lack of ground truth. We will introduce preprocessing pipelines for neural data from multiple modalities, methods for noise reduction, dimensionality reduction, hypothesis testing, spectral analysis, multivariate analysis, and graph theory. At the end of this course, students will be ready to analyze neural data from various recording techniques.