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Course 1: The Data Scientist’s Toolbox

Upcoming Session: 2 June, 7 July
Duration: 4 weeks
Estimated Workload: 3-4 hours/week
URL: https://www.coursera.org/course/datascitoolbox
Description: Upon completion of this course you will be able to identify and classify data science problems. You will also have created your Github account, created your first repository, and pushed your first markdown file to your account.

Course 2: R Programming
Upcoming Session: 2 June, 7 July
Duration: 4 weeks
Estimated Workload: 3-5 hours/week
URL: https://www.coursera.org/course/rprog
Description: The course will cover the following material each week:
Week 1: Overview of R, R data types and objects, reading and writing data
Week 2: Control structures, functions, scoping rules, dates and times
Week 3: Loop functions, debugging tools
Week 4: Simulation, code profiling

Course 3: Getting and Cleaning Data
Upcoming Session: 2 June, 7 July
Duration: 4 weeks
Estimated Workload: 3-5 hours/week
URL: https://www.coursera.org/course/getdata
Description: Upon completion of this course you will be able to obtain data from a variety of sources. You will know the principles of tidy data and data sharing. Finally, you will understand and be able to apply the basic tools for data cleaning and manipulation.

Course 4: Exploratory Data Analysis
Upcoming Session: 2 June, 7 July
Duration: 4 weeks
Estimated Workload: 3-5 hours/week
URL: https://www.coursera.org/course/exdata
Description: After successfully completing this course you will be able to make visual representations of data using the base, lattice, and ggplot2 plotting systems in R, apply basic principles of data graphics to create rich analytic graphics from different types of datasets, construct exploratory summaries of data in support of a specific question, and create visualizations of multidimensional data using exploratory multivariate statistical techniques.

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