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Курс от Clemson University
courseraПрограммирование
Applied Data Science
Курс от Clemson UniversityО курсе
Being able to extract knowledge from large, complex data sets is one of the most critical skills in today’s data-driven world. This course provides an introduction to fundamental concepts and techniques of Data Science. Learners will learn to combine tools and methods from computer science, statistics, data visualization, and the social sciences to extract knowledge from data. Concepts taught in the course will be illustrated with case studies drawn from fields such as business, public health, and the social sciences. This class focuses on teaching library (e.g, Pandas) based data analysis and model development.
Навыки, которые вы освоите
Model EvaluationRegression AnalysisData ScienceAnomaly DetectionData Visualization SoftwareUnsupervised LearningData CleansingDimensionality ReductionStatistical MethodsDescriptive StatisticsMatplotlibData-Driven Decision-MakingData WranglingPlot (Graphics)Data PreprocessingData AnalysisData MiningStatistical AnalysisPandas (Python Package)Applied Machine Learning
Программа курса
6 модулей · 52 учебных материалов
01Module 1: Data, Statistics, and Visualization14 материалов
Introduction to Applied Data Science
Introduction to Applied Data ScienceВидеоCourse OutlineЧтениеOverview of Course Learning ObjectivesЧтениеLearner Support ResourcesЧтениеУчитесь у экспертов
Tim Ransom
Преподаватель курса