In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

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## 課程信息

### 學生職業成果

## 36%

## 35%

## 11%

### 您將獲得的技能

### 學生職業成果

## 36%

## 35%

## 11%

#### 可分享的證書

#### 100% 在線

#### 可靈活調整截止日期

#### 中級

You should have beginner level experience in Python. Familarity with regression is recommended.

#### 完成時間大約為21 小時

#### 英語（English）

## 教學大綱 - 您將從這門課程中學到什麼

**完成時間為 25 小時**

## Week 1: Background, Getting Started, and Nuts & Bolts

This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.

**完成時間為 25 小時**

**28 個視頻**

**9 個閱讀材料**

**1 個練習**

**完成時間為 12 小時**

## Week 2: Programming with R

Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.

**完成時間為 12 小時**

**13 個視頻**

**3 個閱讀材料**

**2 個練習**

**完成時間為 10 小時**

## Week 3: Loop Functions and Debugging

We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice.

**完成時間為 10 小時**

**8 個視頻**

**2 個閱讀材料**

**1 個練習**

**完成時間為 11 小時**

## Week 4: Simulation & Profiling

This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R.

**完成時間為 11 小時**

**6 個視頻**

**4 個閱讀材料**

**2 個練習**

### 審閱

#### 4.6

##### 來自R 语言程序设计（中文版）的熱門評論

Excellent course! I already knew a lot about R - but this class helped me solidify what I already knew, taught me lots of new tricks, and now I have a certificate that says I know `something' about R!

Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.

"R Programming" forces you to dive in deep.\n\nThese skills serve as a strong basis for the rest of the data science specialization.\n\nMaterial is in depth, but presented clearly. Highly recommended!

Excelente opportunity to learn a lot. The course is very well prepared introduce you to R programing. Dont feel bad if you dont get it at te first moment. It will be a process of leaning worth trying

This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox.\n\nThis is perhaps the best course on R Programming designed for a small duration.

The content is superbly designer for a beginner. The Swirl assignments need to make compulsory. Infact they contributed more to the learning process. More Swirl contents will make the course richer.

The course was a wonderful introduction to R, though I felt the programming projects were lacking a bit in terms of direction. Definitely go through the swirl exercises to help reinforce everything!

Great course for people who work with data a lot.\n\nThis course actually helps in looking at data in its basic forms, helps understand transformations better, and gives ideas about playing with it.

I am pleasantly surprised with the quality of this course. For a beginner, the Swirl exercises are incredibly helpful and I was able to build confidence in working with R because of them. Thank you!

A great introduction to slightly more complicated R programming. Basic concepts covered well and it builds nicely to the point where you feel like you can apply your knowledge to real world examples

Helpful in learning the basics and then some. However, the course assumes you know certain things about the R language and a lot of catching up had to be done (learning from outside sources etc.).

Quite good if you can cope with the pace. Absolute beginners may struggle. But exercises were challenging enough to make you learn and that's the best part of the course including Swirl Exercises.

This course was almost excellent. The tutorials were amazing. I am just going to complain about Assignment 2; inverted matrices weren't a pre-requisite so it was hard to understand that assignment

This is a very thorough introduction to R. There are plenty of exercises to quickly get familiar with the language. Some good guided assignments really help getting familiar with coding functions.

This course fully meets my expectations. It provides a concise starting point and even manages to introduce advanced concepts such as the 'apply' family. The final assignment is fully appropriate.

The Week 3 programming assignment didn't feel helpful at all. At least, I didn't feel like I used anything I had learned so far. Just practiced Git, which I'm already relatively comfortable with.

Found lectures to be only somewhat helpful. More engaging production as opposed to just voice over ppt would be much better. Learning tools could also be improved to take advantage of technology.

For anyone planning to set their foot in the vast field of data analytics and R, this course is what will set the momentum and actually make you fond of programming in R by the end of the course.

Solid course overall. The instructions and in-class coding examples are clear and easy to follow.\n\nOnly drawback is that the programming assignments are somewhat disconnected from the content.

The course is good however I felt the programming assignments were too difficult compared to lectures. Which however makes us work hard and refer to a lot of solutions to arrive at our solutions

### 提供方

#### 约翰霍普金斯大学

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

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