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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
Gianfranco Campana
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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JHU Data Science specialization_certificate

  • 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 Gianfranco Campana 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.