coursera data science 2015

1
10 Courses The Data Scientist’s Toolbox R Programming Getting and Cleaning Data Exploratory Data Analysis Reproducible Research Statistical Inference Regression Models Practical Machine Learning Developing Data Products Data Science Capstone Brian Caffo, PhD, MS Department of Biostatistics Johns Hopkins Bloomberg School of Public Health Jeffrey Leek, PhD Department of Biostatistics Johns Hopkins Bloomberg School of Public Health Roger D. Peng, PhD Department of Biostatistics Johns Hopkins Bloomberg School of Public Health SUDHIR KUDIKALA has successfully completed the online, non-credit Specialization Data Science A sequence of nine 4-week courses followed by a culminating 8-week project. The Data Science Specialization covers the concepts and tools for an entire data science pipeline. Successful participants learn how to use the tools of the trade, think analytically about complex problems, manage large data sets, deploy statistical principles, create visualizations, build and evaluate machine learning algorithms, publish reproducible analyses, and develop data products. View this certificate on Coursera . This certificate does not confer academic credit toward a degree or official status at the Johns Hopkins University.

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Page 1: Coursera Data Science 2015

10 Courses

The Data Scientist’s Toolbox

R Programming

Getting and Cleaning Data

Exploratory Data Analysis

Reproducible Research

Statistical Inference

Regression Models

Practical Machine Learning

Developing Data Products

Data Science Capstone

Brian Caffo, PhD, MS

Department of

Biostatistics

Johns Hopkins

Bloomberg School of

Public Health

Jeffrey Leek, PhD

Department of

Biostatistics

Johns Hopkins

Bloomberg School of

Public Health

Roger D. Peng, PhD

Department of

Biostatistics

Johns Hopkins

Bloomberg School of

Public Health

SUDHIR KUDIKALAhas successfully completed the online, non-credit Specialization

Data ScienceA sequence of nine 4-week courses followed by a culminating8-week project.

The Data Science Specialization covers the concepts and tools foran entire data science pipeline. Successful participants learn howto use the tools of the trade, think analytically about complexproblems, manage large data sets, deploy statistical principles,create visualizations, build and evaluate machine learningalgorithms, publish reproducible analyses, and develop dataproducts.

View this certificate on Coursera.

This certificate does not confer academic credit toward a degree or official status at the Johns Hopkins University.