Carolina Data World

Fundamentals of Python Programming serves to teach students the basic concepts of computer science, equipping them with a solid foundation in programming and problem-solving skills. The course is structured to accommodate beginners with little to no programming experience while offering challenges for those who have already been exposed to basic coding concepts.

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This course introduces students to the foundational concepts and techniques in data visualization and statistical graphics. It aims to equip students with practical skills to effectively communicate complex quantitative information through visual means. Participants will learn how to create, interpret, and critically evaluate a variety of data visualizations using modern software tools.

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Web scraping is the process of collecting and parsing raw data from the Web, and the Python community has come up with some pretty powerful web scraping tools. The Internet hosts perhaps the greatest source of information on the planet. Many disciplines, such as data science, business intelligence, and investigative reporting, can benefit enormously from collecting and analyzing data from websites.

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The practical application of machine learning requires understanding the underlying theoretical assumptions behind a wide variety of statistical models, how to analyze the performance of such models, and how to integrate models into data processing pipelines. This course introduces students to a broad survey of supervised and unsupervised machine learning methods, including fundamentals in the setup and evaluation of linear and non-linear statistical models.

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