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Advanced Practical Course Data Science for Computer Networks (Winter 2017/2018): Difference between revisions
Advanced Practical Course Data Science for Computer Networks (Winter 2017/2018) (view source)
Revision as of 12:06, 15 September 2017
, 15 September 2017→Prerequisites
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==Prerequisites== | ==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 Coursera Course "Machine Learning" by Stanford University) before entering this course. You need to be familiar with basic statistics (distributions, p/t/z-tests, etc.) and a range of machine learning algorithms (linear/logistic/lasso regression, k-means clustering, k-NN classification etc.). | *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 Coursera Course "Machine Learning" by Stanford University) before entering this course. You need to be familiar with basic statistics (distributions, p/t/z-tests, etc.) and a range of machine learning algorithms (linear/logistic/lasso regression, k-means clustering, k-NN classification etc.). | ||
*Knowledge of Python or R | *Knowledge of Python or R | ||
==Preliminary Schedule== | ==Preliminary Schedule== | ||