This course is a practical introduction for those interested in learning Python for a wide variety of applications and use cases. The material has been designed to expose you to common techniques and tools you'll be able to exercise immediately. This course assumes no prior development experience and ranges from beginning to intermediate Python concepts including: creating a Python environment, data types, operators/expressions, data and control structures, conditional statements, classes/objects, functions, multi-threaded applications, testing and deployment tools, REST API's, machine learning, and more. You'll also gain valuable experience with tools like PyCharm/ VSCode, Jupyter Notebooks, Git, PyLint, PyDocs/Doxygen, and many more. Each concept is accompanied by real code samples that will be explained in-detail and the assignments will present you with interesting scientific problems to enable you to practice your Python skills for the purpose of solving real, complex problems. The course is textbook-free and provides a number of hand-chosen readings to supplement the lecture materials. Upon completion of the course you will be equipped with knowledge of the skills and tools to begin tackling problems the Pythonic way.Prerequisite(s): One year of college mathematics.Course Note(s): Not for graduate credit. A programming methodology course is needed for admission to the Artificial Intelligence or Data Science. Students who lack this prerequisite can fulfill admission requirements by completing this course with a grade of B– or better
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