關於此課程：This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Because every data science environment encounters unique data challenges, there is always a need to develop custom software specific to your organization’s mission. You will also be able to define new data types in R and to develop a universe of functionality specific to those data types to enable cleaner execution of data science tasks and stronger reusability within a team.
製作方： Johns Hopkins University
教學方： Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health教學方： Brooke Anderson, Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University
| 基本信息 | 課程 2（共 5 門，Mastering Software Development in R Specialization ） |
| 級別 | 中級 |
| 語言 | English, 字幕：Chinese (Simplified) |
| 如何通過 | 通過所有計分作業以完成課程。 |
| 用戶評分 |
授課大綱
第 1 週
Welcome to Advanced R Programming
This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Because every data science environment encounters unique data challenges, there is always a need to develop custom software specific to your organization’s mission. You will also be able to define new data types in R and to develop a universe of functionality specific to those data types to enable cleaner execution of data science tasks and stronger reusability within a team.
1 個視頻, 3 個閱讀材料
- Reading: Syllabus
- Reading: Course Textbook: Mastering Software Development in R
- Reading: swirl Assignments
Functions
This module begins with control structures in R for controlling the logical flow of an R program. We then move on to functions, their role in R programming, and some guidelines for writing good functions.
17 個閱讀材料
- Reading: Control Structures Overview
- Reading: if-else
- Reading: for Loops
- Reading: Nested for loops
- Reading: next, break
- Reading: Summary
- Reading: Functions Overview
- Reading: Code
- Reading: Function interface
- Reading: Default values
- Reading: Re-factoring code
- Reading: Dependency Checking
- Reading: Vectorization
- Reading: Argument Checking
- Reading: R package
- Reading: When Should I Write a Function?
- Reading: Summary
已評分: Swirl Lesson
第 2 週
Functional Programming
Functional programming is a key aspect of R and is one of R's differentiating factors as a data analysis language. Understanding the concepts of functional programming will help you to become a better data science software developer. In addition, we cover error and exception handling in R for writing robust code.
19 個閱讀材料
- Reading: What is Functional Programming?
- Reading: Core Functional Programming Functions
- Reading: Map
- Reading: Reduce
- Reading: Search
- Reading: Filter
- Reading: Compose
- Reading: Partial Application
- Reading: Side Effects
- Reading: Recursion
- Reading: Summary
- Reading: Expressions
- Reading: Environments
- Reading: Execution Environments
- Reading: What is an error?
- Reading: Generating Errors
- Reading: When to generate errors or warnings
- Reading: How should errors be handled?
- Reading: Summary
已評分: Swirl Lesson
第 3 週
Debugging and Profiling
Debugging tools are useful for analyzing your code when it exhibits unexpected behavior. We go through the various debugging tools in R and how they can be used to identify problems in code. Profiling tools allow you to see where your code spends its time and to optimize your code for maximum efficiency.
15 個閱讀材料
- Reading: Debugging Overview
- Reading: traceback()
- Reading: Browsing a Function Environment
- Reading: Tracing Functions
- Reading: Using debug() and debugonce()
- Reading: recover()
- Reading: Final Thoughts on Debugging
- Reading: Summary
- Reading: Profiling Overview
- Reading: microbenchmark
- Reading: profvis
- Reading: Find out more
- Reading: Summary
- Reading: Non-standard evaluation
- Reading: Summary
已評分: Debugging and Profiling
第 4 週
Object-Oriented Programming
Object oriented programming allows you to define custom data types or classes and a set of functions for handling that data type in a way that you define. R has a three different methods for implementing object oriented programming and we will cover them in this section.
11 個閱讀材料
- Reading: OOP Overview
- Reading: Object Oriented Principles
- Reading: S3
- Reading: S4
- Reading: Reference Classes
- Reading: Summary
- Reading: Overview
- Reading: Reuse existing data structures
- Reading: Compose simple functions with the pipe
- Reading: Embrace functional programming
- Reading: Design for humans
已評分: Functional and Object-Oriented Programming
常見問題解答
運作方式
Задания курса
Каждый курс — это интерактивный учебник, который содержит видеоматериалы, тесты и проекты.
Помощь сокурсников
Общайтесь с тысячами других учащихся: обсуждайте идеи, материалы курса и помогайте друг другу осваивать новые понятия.
Сертификаты
Получите документы о прохождении курсов и поделитесь своим успехом с друзьями, коллегами и работодателями.
製作方
Johns Hopkins University
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.
價格
| 購買課程 | |
|---|---|
| 訪問課程材料 | 可用 |
| 訪問評分的材料 | 可用 |
| 收到最終成績 | 可用 |
| 獲得可共享的課程證書 | 可用 |
評分和審閱
It is a short and good R course. It goes right to the more advanced stuff. Even a long time user of R will learn new things. The final project is revised by the same students which in my opinion makes it more of a challenge. I've never wanted a homework to be as perfect as this one.
Great course. Challenging and I learn a lot of new techniques to improve my R skills.
Excellent subject matter. 4 stars instead of 5 is only because there was no video. I love the videos in the other courses in this track, since I am an auditory learner.
HM
Much of this course is well-constructed, well-communicated and clear. Sections from weeks 1-3 were attuned to my programming skill level and the material was communicated generally so that those with experience in other languages could also follow along easily. I had no technical problems with submitting assignments or quizzes and I found the assignments with swirl to be effective in reinforcing the material from the readings. My biggest criticism of this course is about Week 4's content and its respective part in the final assignment. The content in Week 4 concerns Object-Oriented programming and this material was really hard to absorb. It seemed to come out of left field and the readings did not feel as clear as they were in other sections. The readings essentially say "Here is what object-oriented programming allows you to do [create/manipulate classes and objects]" but then goes back on itself by recommending that you do not use object-oriented programming to create custom classes or data structures because the R community already knows what data structures they like. Personally, I had a lot of trouble understanding this content because it was so briefly explained. This did not help me by the time I had to complete the object-oriented programming portion of the final assignment. It is very clear from the class forums that other students have found that section of the assignment particularly difficult for years. Overall, this course was excellent in teaching functional programming principles and application, but the object-oriented section slightly spoiled my experience of the course.