In this course, students will learn the most essential aspects of python programming. The topics are tailored towards data analysis; no prior programming experience is required. We will cover variables, data types and data structures, data frames, conditionals, loops, and functions. We will also cover reading and writing raw files, and the core APIs in analysis and visualization. Beyond these foundations, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for analysis and reporting. These packages will facilitate workflow and enhance the basic Python functionalities; using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. During this module, students solidify their new skills by applying the concepts they have learned to the analysis of several datasets. They will be given the opportunity to live-code during the sessions and troubleshoot their code with classmates and the instructor. Students will walk out of this bootcamp with newly-forged Python coding skills, knowledge of several of the most important data science libraries and tools, and have the resources in hand for learning more. 1.5 cr