├── img ├── author_image.png └── shield_image.png ├── chapter6.md ├── course.yml ├── chapter1.md ├── chapter3.md ├── chapter5.md ├── chapter4.md ├── chapter2.md └── README.md /img/author_image.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datacamp/community-courses-r-for-the-intimidated/master/img/author_image.png -------------------------------------------------------------------------------- /img/shield_image.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datacamp/community-courses-r-for-the-intimidated/master/img/shield_image.png -------------------------------------------------------------------------------- /chapter6.md: -------------------------------------------------------------------------------- 1 | --- 2 | title : Final Project 3 | description : In this last chapter, you will combine everything you've learned in this course to work on a final project using the volcanoes dataset. 4 | attachments : 5 | slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf 6 | 7 | --- type:VideoExercise lang:r xp:50 skills:1 key:d461063ad841592b7433e485c182f7440116ed9e 8 | ## Final project 9 | 10 | *** =video_link 11 | //player.vimeo.com/video/160903443 -------------------------------------------------------------------------------- /course.yml: -------------------------------------------------------------------------------- 1 | title : R for the Intimidated 2 | author_field : Annika Salzberg 3 | description : This course will introduce you to the very basics of R from running simple functions to manipulating datasets and creating graphs. This course is designed for people with very little or no programming experience at all. 4 | author_bio : Annika Salzberg is a student at Cornell University majoring in Entomology, with a strong interest in computer science. She taught a class on R in high school, and subsequently created a video course targeted towards students with minimal to no prior programming experience. She strongly believes that anyone can learn programming, and everyone should give it a try! 5 | university : DataCamp 6 | difficulty_level : 1 7 | time_needed : 2 hours 8 | -------------------------------------------------------------------------------- /chapter1.md: -------------------------------------------------------------------------------- 1 | --- 2 | title : Introduction to Course and RStudio 3 | description : This chapter contains videos that walks you through what a programming language is, and how to install RStudio on your computer. 4 | attachments : 5 | slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf 6 | 7 | --- type:VideoExercise lang:r xp:50 skills:1 key:c630831c49054fdc8c800e4d40f7bba83e92de27 8 | ## Introduction to this course 9 | 10 | *** =video_link 11 | //player.vimeo.com/video/160903486 12 | 13 | --- type:VideoExercise lang:r xp:50 skills:1 key:d67531ae21e9395c4f56fc4d4c7d430e4782421a 14 | ## Introduction to programming 15 | 16 | *** =video_link 17 | //player.vimeo.com/video/160903457 18 | 19 | --- type:VideoExercise lang:r xp:50 skills:1 key:4a9c99a2bc5095a2fd61106cbdf6b3a797ff2fcb 20 | ## Installing R and RStudio 21 | 22 | *** =video_link 23 | //player.vimeo.com/video/160903444 24 | 25 | --- type:VideoExercise lang:r xp:50 skills:1 key:2a82f335b729691409857ea04deb731350bcb8af 26 | ## Walkthrough of RStudio 27 | 28 | *** =video_link 29 | //player.vimeo.com/video/160903475 -------------------------------------------------------------------------------- /chapter3.md: -------------------------------------------------------------------------------- 1 | --- 2 | title : Installing Packages, Importing and Cleaning Data 3 | description : In this chapter, you'll be introduced to some of the most popular packages in R, learn how to import your dataset, and some techniques to clean your dataset! 4 | attachments : 5 | slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf 6 | 7 | --- type:VideoExercise lang:r xp:50 skills:1 key:e8a7eda1305509de26a004a1f59b6645c2d193af 8 | ## Packages 9 | 10 | *** =video_link 11 | //player.vimeo.com/video/160903466 12 | 13 | --- type:VideoExercise lang:r xp:50 skills:1 key:7d8a4d1c08292dfa5f10902a6b021ad40d1b5d7e 14 | ## Interlude: download! 15 | 16 | *** =video_link 17 | //player.vimeo.com/video/160903483 18 | 19 | --- type:VideoExercise lang:r xp:50 skills:1 key:8781857b03ef2e4a13e735902dd1778d71415788 20 | ## Importing data 21 | 22 | *** =video_link 23 | //player.vimeo.com/video/160903440 24 | 25 | --- type:VideoExercise lang:r xp:50 skills:1 key:390088242e09b3b48dd1ec9f4c67fe7005fd5854 26 | ## Missing values - scrub & replace 27 | 28 | *** =video_link 29 | //player.vimeo.com/video/160903447 -------------------------------------------------------------------------------- /chapter5.md: -------------------------------------------------------------------------------- 1 | --- 2 | title : Data Manipulation 3 | description : In this chapter, you'll learn how to manipulate your data in order to not only make better graphs, but also making your data graphable in the first place. 4 | attachments : 5 | slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf 6 | 7 | --- type:VideoExercise lang:r xp:50 skills:1 key:70c3e1865b32d1a909070f6e5a6794017b0854cd 8 | ## ddply: Part one 9 | 10 | *** =video_link 11 | //player.vimeo.com/video/160903462 12 | 13 | --- type:VideoExercise lang:r xp:50 skills:1 key:bf5e3b5a9e77cc9178eadc90aaa07148f4384f9c 14 | ## ddply: Part two 15 | 16 | *** =video_link 17 | //player.vimeo.com/video/160903450 18 | 19 | --- type:VideoExercise lang:r xp:50 skills:1 key:f365d065a274004e59ab275d450ed17f03b96397 20 | ## ddplr: Part three 21 | 22 | *** =video_link 23 | //player.vimeo.com/video/160903485 24 | 25 | --- type:VideoExercise lang:r xp:50 skills:1 key:cbfc91186882326518e0ddb1bbd18a98db2bd65b 26 | ## melt: Part one 27 | 28 | *** =video_link 29 | //player.vimeo.com/video/160903448 30 | 31 | --- type:VideoExercise lang:r xp:50 skills:1 key:0e6858f969da969ee6e9f704e9edc15262fa51a4 32 | ## melt: Part two 33 | 34 | *** =video_link 35 | //player.vimeo.com/video/160903461 -------------------------------------------------------------------------------- /chapter4.md: -------------------------------------------------------------------------------- 1 | --- 2 | title : Data Visualization Techniques 3 | description : In this chapter, you'll learn about the syntax to make data visualizations using some of R's most popular graphics packages. 4 | attachments : 5 | slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf 6 | 7 | --- type:VideoExercise lang:r xp:50 skills:1 key:169d19f6e769a754bc13398d94dc967f8031aa8c 8 | ## Plotting matrices 9 | 10 | *** =video_link 11 | //player.vimeo.com/video/160903488 12 | 13 | --- type:VideoExercise lang:r xp:50 skills:1 key:836b51c3091735a05140c47d3e4a6bab27f5cbb3 14 | ## Scatterplots: R graphics 15 | 16 | *** =video_link 17 | //player.vimeo.com/video/160903470 18 | 19 | --- type:VideoExercise lang:r xp:50 skills:1 key:5b968bcd163ddf48294329bf02ded8f933149d78 20 | ## ggplot2: Syntax 21 | 22 | *** =video_link 23 | //player.vimeo.com/video/160903471 24 | 25 | --- type:VideoExercise lang:r xp:50 skills:1 key:3408ff96a3765af1c87d4c3b30451df94ea22fb4 26 | ## ggplot2: Scatterplots 27 | 28 | *** =video_link 29 | //player.vimeo.com/video/160903460 30 | 31 | --- type:VideoExercise lang:r xp:50 skills:1 key:d8bd66caf4a76a06979610610b041e8cd7cbd4a8 32 | ## ggplot2: Bar graphs 33 | 34 | *** =video_link 35 | //player.vimeo.com/video/160903484 36 | 37 | --- type:VideoExercise lang:r xp:50 skills:1 key:6937b2fab933b28fe16c3ee46406f4feedc53d5f 38 | ## ggplot2: Histograms 39 | 40 | *** =video_link 41 | //player.vimeo.com/video/160903442 42 | 43 | --- type:VideoExercise lang:r xp:50 skills:1 key:15d1bee2f0d5cdfa70966cb72a70b9b60d2fbb7f 44 | ## ggplot2: Density plots 45 | 46 | *** =video_link 47 | //player.vimeo.com/video/160903451 -------------------------------------------------------------------------------- /chapter2.md: -------------------------------------------------------------------------------- 1 | --- 2 | title : Getting Started With Data Structures in R 3 | description : In this chapter, you'll be introduced to some basic functions and data structures. 4 | attachments : 5 | slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf 6 | 7 | --- type:VideoExercise lang:r xp:50 skills:1 key:353320a49417f2fa84e241579d8ac8b893c34ae4 8 | ## Types of data and basic functions 9 | 10 | *** =video_link 11 | //player.vimeo.com/video/160903479 12 | 13 | --- type:VideoExercise lang:r xp:50 skills:1 key:aeefe740dc02426e6071091acb4f0f5fba7b1e58 14 | ## Naming objects 15 | 16 | *** =video_link 17 | //player.vimeo.com/video/160903441 18 | 19 | --- type:VideoExercise lang:r xp:50 skills:1 key:4cf303808936881b320366b88c029b686814aaa4 20 | ## Vectors - part 1 21 | 22 | *** =video_link 23 | //player.vimeo.com/video/160903459 24 | 25 | --- type:VideoExercise lang:r xp:50 skills:1 key:c4cda05af7438313d99f85fbd02331712db15941 26 | ## Vectors - part 2 27 | 28 | *** =video_link 29 | //player.vimeo.com/video/160903480 30 | 31 | --- type:VideoExercise lang:r xp:50 skills:1 key:01ed3fe78cc011fc8702ac96b970f4830d561bf0 32 | ## Matrices - part 1 33 | 34 | *** =video_link 35 | //player.vimeo.com/video/160903482 36 | 37 | --- type:VideoExercise lang:r xp:50 skills:1 key:91e876a88d4c54ce396085b7317cc22b599f05b1 38 | ## Matrices - part 2 39 | 40 | *** =video_link 41 | //player.vimeo.com/video/160903473 42 | 43 | --- type:VideoExercise lang:r xp:50 skills:1 key:e14fa7680b2c319cfb87e9f9703dd740a5736268 44 | ## Lists & combining vectors 45 | 46 | *** =video_link 47 | //player.vimeo.com/video/160903474 48 | 49 | --- type:VideoExercise lang:r xp:50 skills:1 key:160f0a2926631d49d93d1e7e81cf35b931697841 50 | ## Subsetting dataframes 51 | 52 | *** =video_link 53 | //player.vimeo.com/video/160903439 54 | 55 | --- type:VideoExercise lang:r xp:50 skills:1 key:1b7d31447d4dd52a0d14f653364613a38a11e35b 56 | ## More dataframes! 57 | 58 | *** =video_link 59 | //player.vimeo.com/video/160903449 -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # DataCamp Template Course 2 | 3 | 4 | 5 | This an automatically generated DataCamp course. Use it as a reference to create your own interactive course. 6 | 7 | Changes you make to this GitHub repository are automatically reflected in the linked DataCamp course. This means that you can enjoy all the advantages of version control, collaboration, issue handling ... of GitHub. 8 | 9 | ## Workflow 10 | 11 | 1. Edit the markdown and yml files in this repository. You can use GitHub's online editor or use git locally and push your changes. 12 | 2. Check out your build attempts on the Teach Dashboard. 13 | 3. Check out your automatically updated course on DataCamp 14 | 15 | ## Getting Started 16 | 17 | A DataCamp course consists of two types of files: 18 | 19 | - `course.yml`, a YAML-formatted file that's prepopulated with some general course information. 20 | - `chapterX.md`, a markdown file with: 21 | - a YAML header containing chapter information. 22 | - markdown chunks representing DataCamp Exercises. 23 | 24 | To learn more about the structure of a DataCamp course, check out the documentation. 25 | 26 | Every DataCamp exercise consists of different parts, read up about them here. A very important part about DataCamp exercises is to provide automated personalized feedback to students. In R, these so-called Submission Correctness Tests (SCTs) are written with the `testwhat` package. SCTs for Python exercises are coded up with `pythonwhat`. Check out the GitHub repositories' wiki pages for more information and examples. 27 | 28 | ## Want to learn more? 29 | - Check out the DataCamp Teach documentation. 30 | - Check out DataCamp's blog posts: 31 | - Create a course with DataCamp Teach 32 | - Interpreting DataCamp Teach's build attempts. 33 | 34 | *Happy teaching!* --------------------------------------------------------------------------------