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coursera-computing-for-data-analysis-r icon coursera-computing-for-data-analysis-r

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.

coursera-dl icon coursera-dl

A script for downloading course material (video's, pdfs, quizzes, etc) from coursera.org

coursera-ml icon coursera-ml

Exercises of Machine Learning Course taught by Prof. Andrew Ng on Coursera.

coursera-statistics-one--r icon coursera-statistics-one--r

Statistics One is designed to be a comprehensive yet friendly introduction to fundamental concepts in statistics. Comprehensive means that this course provides a solid foundation for students planning to pursue more advanced courses in statistics. Friendly means exactly that. The course assumes very little background knowledge in statistics and introduces new concepts with several fun and easy to understand examples. This course is, quite literally, for everyone. If you think you can't learn statistics, this course is for you. If you had a statistics course before but feel like you need a refresher, this course is for you. Even if you are a relatively advanced researcher or analyst, this course provides a foundation and a context that helps to put one’s work into perspective. Statistics One also provides an introduction to the R programming language. All the examples and assignments will involve writing code in R and interpreting R output. R software is free! What this means is you can download R, take this course, and start programming in R after just a few lectures. That said, this course is not a comprehensive guide to R or to programming in general.

courses icon courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

datasciencecoursera icon datasciencecoursera

This is a datasciencecoursera repo , created for the data science courses in coursera.

devdatapeer icon devdatapeer

Course Project for devdataprod-015 on coursera: Shiny Application and Reproducible Pitch.

dynamic-programing icon dynamic-programing

This repo contains code that is classified as "Dynamic Programming" (DP). It contains to implementations of the "Run like Hell" algorithm, one being a naive recursive solution and the second being a super fast, low-cost, graceful DP solution. Comments and testCase file included.

edx-dl icon edx-dl

Simple tool to download videos from edX-based sites

eshop icon eshop

university java course project

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