https://github.com/extwiii/datascience-jhu
Ask the right questions, manipulate data sets, and create visualizations to communicate results - Coursera
https://github.com/extwiii/datascience-jhu
biostatistics data-analysis data-science linear-regression multivariate-regression r r-programming toolbox visualization
Last synced: 3 months ago
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Ask the right questions, manipulate data sets, and create visualizations to communicate results - Coursera
- Host: GitHub
- URL: https://github.com/extwiii/datascience-jhu
- Owner: extwiii
- License: apache-2.0
- Created: 2017-04-16T23:24:27.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2017-04-27T23:13:54.000Z (about 8 years ago)
- Last Synced: 2025-01-28T12:17:07.948Z (5 months ago)
- Topics: biostatistics, data-analysis, data-science, linear-regression, multivariate-regression, r, r-programming, toolbox, visualization
- Homepage:
- Size: 26.4 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DataScience-Johns.Hopkins.University :white_check_mark:
Ask the right questions, manipulate data sets, and create visualizations to communicate results - Coursera
## Course 1 - The Data Scientist’s Toolbox
* Welcome
* Introduction to basic tools
* Installing the Toolbox
* R, Git, Github
* Conceptual Issues
* Steps in a data analysis, Putting the science in data science
* Course Project Submission & Evaluation
## Course 2 - R Programming
* Background, Getting Started, and Nuts & Bolts
* Programming with R
* Derek Franks has written a very nice [tutorial](https://github.com/rdpeng/practice_assignment/blob/master/practice_assignment.rmd) to help you get up to speed
* Loop Functions and Debugging
* lapply, apply, tapply, split, mapply
* Simulation & Profiling
* Simulate a random normal variable with an arbitrary mean and standard deviation
## Course 3 - Getting and Cleaning Data
* Data collection & Data formats
* Raw files (.csv,.xlsx), Databases (mySQL), APIs, Flat files (.csv,.txt), XML, JSON
* Making data tidy
* Distributing data
* Scripting for data cleaning
## Course 4 - Exploratory Data Analysis
* Making exploratory graphs
* Principles of analytic graphics
* Clustering methods
* Dimension reduction techniques
## Course 5 - Reproducible Research
* Concepts, Ideas, & Structure
* Markdown & knitr
* Reproducible Research Checklist & Evidence-based Data Analysis
* Case Studies & Commentaries
## Course 6 - Statistical Inference
* Probability & Expected Values
* Variability, Distribution, & Asymptotics
* Intervals, Testing, & Pvalues
* Power, Bootstrapping, & Permutation Tests
## Course 7 - Regression Models
* Least Squares and Linear Regression
* Linear Regression & Multivariable Regression
* Multivariable Regression, Residuals, & Diagnostics
* Logistic Regression and Poisson Regression
## Course 8 - Practical Machine Learning
* Prediction, Errors, and Cross Validation
* The Caret Package
* Predicting with trees, Random Forests, & Model Based Predictions
* Regularized Regression and Combining Predictors
## Course 9 - Developing Data Products
* Shiny, GoogleVis, and Plotly
* R Markdown and Leaflet
* R Packages
* Swirl and Course Project
The most up to date information on the course lecture notes will always be in the course [Github repository](https://github.com/DataScienceSpecialization/courses)
#### Taught by:
#### Roger D. Peng, PhD - Associate Professor, Biostatistics
#### Brian Caffo, PhD - Professor, Biostatistics
#### Jeff Leek, PhD - Associate Professor, Biostatistics
### Rating :full_moon::full_moon::full_moon::full_moon::full_moon::full_moon::full_moon::new_moon::new_moon::new_moon:
### Difficulty :full_moon::full_moon::full_moon::full_moon::full_moon::full_moon::new_moon::new_moon::new_moon::new_moon:
### Created By Bilal Cagiran | [E-Mail](mailto:[email protected]) | [Github](https://github.com/extwiii/) | [LinkedIn](https://linkedin.com/in/bilalcagiran) | [CodePen](http://codepen.io/extwiii/) | [Blog/Site](http://bilalcagiran.com) | [FreeCodeCamp](https://www.freecodecamp.com/extwiii)