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Data Wrangling with MongoDB (Udacity) 0 个评论 关注

开始时间: 随时 持续时间: 自主

主页: https://www.udacity.com/course/ud032

简介: This is one of the first courses we offer for students interested in the emerging field of data science.

In this course, we will explore how to wrangle data from diverse sources and shape it to enable data-driven applications. Some data scientists spend the bulk of their time doing this!

Students will learn how to collect, clean, and extract needed data and store it in MongoDB. We will also cover schema design, learn how to process data within MongoDB, and utilize Hadoop along with MongoDB to perform MapReduce operations.

This is a great course for those interested in entry-level data analyst positions as well as current business/data analysts looking to add big data to their repertoire, and managers working with data professionals or looking to leverage big data.

Mining Massive Datasets (Coursera) 1 个评论 关注

开始时间: 09/12/2015 持续时间: 7 weeks

主页: https://www.coursera.org/course/mmds

简介: This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well.

StatLearning: Statistical Learning (Stanford Online) 3 个评论 关注

开始时间: 01/20/2014 持续时间: 未知

主页: https://class.stanford.edu/courses/HumanitiesScience/StatLearning/Winter2014/about

简介: This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical).

Machine Learning (Coursera) 28 个评论 关注

开始时间: 待定 持续时间: Unknown

主页: https://www.coursera.org/course/ml

简介: Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.