Informações sobre o curso: 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.
Para quem é direcionado este curso: Some programming experience (in any language) is recommended.
Desenvolvido por: Johns Hopkins University
Ministrado por: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public HealthMinistrado por: Jeff Leek, PhD, Associate Professor, Biostatistics
Bloomberg School of Public HealthMinistrado por: Brian Caffo, PhD, Professor, Biostatistics
Bloomberg School of Public Health
| Informações básicas | Curso 2 de 10 no Data Science Specialization |
| Nível | Intermediário |
| Idioma | English, Legendas: French, Chinese (Simplified), Vietnamese, Japanese |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
Programa
SEMANA 1
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.
28 videos, 9 leituras
- Reading: Welcome to R Programming
- Reading: About the Instructor
- Reading: Pre-Course Survey
- Reading: Syllabus
- Reading: Course Textbook
- Reading: Course Supplement: The Art of Data Science
- Reading: Data Science Podcast: Not So Standard Deviations
- Vídeo: Installing R on Windows
- Vídeo: Installing R Studio (Mac)
- Vídeo: Writing Code / Setting Your Working Directory (Windows)
- Vídeo: Writing Code / Setting Your Working Directory (Mac)
- Reading: Getting Started and R Nuts and Bolts
- Vídeo: Introduction
- Vídeo: Overview and History of R
- Vídeo: Getting Help
- Vídeo: R Console Input and Evaluation
- Vídeo: Data Types - R Objects and Attributes
- Vídeo: Data Types - Vectors and Lists
- Vídeo: Data Types - Matrices
- Vídeo: Data Types - Factors
- Vídeo: Data Types - Missing Values
- Vídeo: Data Types - Data Frames
- Vídeo: Data Types - Names Attribute
- Vídeo: Data Types - Summary
- Vídeo: Reading Tabular Data
- Vídeo: Reading Large Tables
- Vídeo: Textual Data Formats
- Vídeo: Connections: Interfaces to the Outside World
- Vídeo: Subsetting - Basics
- Vídeo: Subsetting - Lists
- Vídeo: Subsetting - Matrices
- Vídeo: Subsetting - Partial Matching
- Vídeo: Subsetting - Removing Missing Values
- Vídeo: Vectorized Operations
- Vídeo: Introduction to swirl
- Reading: Practical R Exercises in swirl Part 1
- Ungraded Programming: swirl Lesson 1: Basic Building Blocks
- Ungraded Programming: swirl Lesson 2: Workspace and Files
- Ungraded Programming: swirl Lesson 3: Sequences of Numbers
- Ungraded Programming: swirl Lesson 4: Vectors
- Ungraded Programming: swirl Lesson 5: Missing Values
- Ungraded Programming: swirl Lesson 6: Subsetting Vectors
- Ungraded Programming: swirl Lesson 7: Matrices and Data Frames
Nota atribuída: Week 1 Quiz
SEMANA 2
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.
13 videos, 3 leituras
- Reading: Week 2: Programming with R
- Vídeo: Control Structures - If-else
- Vídeo: Control Structures - For loops
- Vídeo: Control Structures - While loops
- Vídeo: Control Structures - Repeat, Next, Break
- Vídeo: Your First R Function
- Vídeo: Functions (part 1)
- Vídeo: Functions (part 2)
- Vídeo: Scoping Rules - Symbol Binding
- Vídeo: Scoping Rules - R Scoping Rules
- Vídeo: Scoping Rules - Optimization Example (OPTIONAL)
- Vídeo: Coding Standards
- Vídeo: Dates and Times
- Reading: Practical R Exercises in swirl Part 2
- Ungraded Programming: swirl Lesson 1: Logic
- Ungraded Programming: swirl Lesson 2: Functions
- Ungraded Programming: swirl Lesson 3: Dates and Times
- Reading: Programming Assignment 1 INSTRUCTIONS: Air Pollution
Nota atribuída: Week 2 Quiz
Nota atribuída: Programming Assignment 1: Quiz
SEMANA 3
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.
8 videos, 2 leituras
- Reading: Week 3: Loop Functions and Debugging
- Vídeo: Loop Functions - apply
- Vídeo: Loop Functions - mapply
- Vídeo: Loop Functions - tapply
- Vídeo: Loop Functions - split
- Vídeo: Debugging Tools - Diagnosing the Problem
- Vídeo: Debugging Tools - Basic Tools
- Vídeo: Debugging Tools - Using the Tools
- Reading: Practical R Exercises in swirl Part 3
- Ungraded Programming: swirl Lesson 1: lapply and sapply
- Ungraded Programming: swirl Lesson 2: vapply and tapply
Nota atribuída: Week 3 Quiz
Nota atribuída: Programming Assignment 2: Lexical Scoping
SEMANA 4
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.
6 videos, 4 leituras
- Reading: Week 4: Simulation & Profiling
- Vídeo: Simulation - Generating Random Numbers
- Vídeo: Simulation - Simulating a Linear Model
- Vídeo: Simulation - Random Sampling
- Vídeo: R Profiler (part 1)
- Vídeo: R Profiler (part 2)
- Reading: Practical R Exercises in swirl Part 4
- Ungraded Programming: swirl Lesson 1: Looking at Data
- Ungraded Programming: swrl Lesson 2: Simulation
- Ungraded Programming: swirl Lesson 3: Base Graphics
- Reading: Programming Assignment 3 INSTRUCTIONS: Hospital Quality
- Reading: Post-Course Survey
Nota atribuída: Week 4 Quiz
Nota atribuída: Programming Assignment 3: Quiz
Perguntas frequentes
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Johns Hopkins University
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Custo
| Comprar curso | |
|---|---|
| Acesso aos materiais do curso | Disponível |
| Acesso a materiais valendo nota | Disponível |
| Receba uma nota final | Disponível |
| Obtenha um Certificado de Curso compartilhável | Disponível |
Classificações e avaliações
I bit more examples would be nice
Excelent experience so far.
Hard assignments which made me work like mad! I think it gave me a good rigorous beginning to learning R.
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Good overview of base R and its application.