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Data Science in Smart City (Summer 2022): Difference between revisions
Data Science in Smart City (Summer 2022) (view source)
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Students need to finish three tasks by specific deadlines throughout the course. Note that this course thus requires a continuous effort throughout the whole semester. | Students need to finish three tasks by specific deadlines throughout the course. Note that this course thus requires a continuous effort throughout the whole semester. | ||
A final report needs to be submitted at the end of the semester. | A final report needs to be submitted at the end of the semester. | ||
==Prerequisites== | |||
*You are ''highly recommended'' to have completed a course on Data Science (e.g., "[https://www.swe.informatik.uni-goettingen.de/lectures/data-science-and-big-data-analytics-ws2015 Data Science and Big Data Analytics" taught by Dr. Steffen Herbold] or the Course "Machine Learning" by Stanford University) before entering this course. You need to be familiar with basic statistics (distributions, p/t/z-tests, etc.), a range of machine learning algorithms (linear/logistic/lasso regression, k-means clustering, k-NN classification etc.), computer networking, and mobile communications. | |||
*Knowledge of any of the following languages: Python (course language), R, Matlab or any language that features proper machine learning libraries | |||
==Schedule== | ==Schedule== | ||