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Reproducible Templates for Analysis and Dissemination

Approx. 20 hours to complete

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Course Summary

This course teaches students how to create reproducible templates and perform data analysis on them. It covers various tools and techniques to help simplify the process and make it more efficient.

Key Learning Points

Learn how to create reproducible templates for data analysis
Understand the importance of automation and how to implement it in your workflows
Gain hands-on experience in using tools like R Markdown and Git to streamline your work

Learning Outcomes

Understand the importance of reproducibility in data analysis
Learn how to create and use reproducible templates using R Markdown
Develop skills in Git for version control and collaboration

Prerequisites or good to have knowledge before taking this course

Basic knowledge of R programming language
Familiarity with data analysis concepts and techniques

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced
Video lectures
Hands-on projects

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Data Analysis and Presentation Skills: the PwC Approach
Data Science Methodology

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Description

This course will assist you with recreating work that a previous coworker completed, revisiting a project you abandoned some time ago, or simply reproducing a document with a consistent format and workflow. Incomplete information about how the work was done, where the files are, and which is the most recent version can give rise to many complications. This course focuses on the proper documentation creation process, allowing you and your colleagues to easily reproduce the components of your workflow. Throughout this course, you'll receive helpful demonstrations of RStudio and the R Markdown language and engage in active learning opportunities to help you build a professional online portfolio.

Outline

Introduction to Reproducible Research and Dynamic Documentation
Welcome and an Introduction to the Course
Welcome to Week 1!
History and Importance of Reproducibility
Dynamic Documentation and Literate Programming
Components and Examples of Reproducibility
R and RStudio Introduction
Git and Github - Part 1
Git and Github - Part 2
Git and Github - Part 3
Creating Your First Document
Wrap-Up
Course Outline and Grading Information
Articles, Resources, and File Organization Examples
[Lecture Prep] - Links for R and RStudio
R and RStudio Resources
[Lecture Prep] - GIT and GitHub
Books on Reproducibility and Tools of the Trade
Practice
Week 1

R Markdown: Syntax, Document, and Presentation Formats
Welcome to Week 2!
Introduction to R Markdown and the YAML Header
R Markdown Syntax
Figures, Tables, and Equations
Images, Videos, and Footnotes
Presentation Formats
Book Format
Wrap-Up
[Lecture Prep] - Links for R Markdown and YAML
[Lecture Prep] - R Markdown File
R Markdown Resources
Resources for Tables and Equations
[Lecture Prep] - Media and R Markdown Files
Resource for Embedding Videos
[Lecture Prep] - R Markdown File
Resources for the Presentation Format
[Lecture Prep] - Link for Bookdown Demo
Resources for the Book Format
[Graded Quiz Prep] - Week 2 Instructions
Practice
Week 2

R Markdown Templates: Processing and Customizing
Week 3 Introduction
Customizing an HTML Document
Customizing a WORD Document
Customizing Other Document Formats
Working with R Packages
Building a Document Template, Part 1
Building a Document Template, Part 2
Adding Parameters in a Document Template
Wrap-Up
[Lecture Prep] - CSS File
Note on MD files
Resources for Customizing Documents
[Lecture Prep] - R Script File
[Lecture Prep] - Code File
Resources for Parameters and Template Development
Practice
Week 3

Leveraging Custom Templates from Leading Scientific Journals
Week 4 Introduction
Examples and Demo of Existing Templates
Exploring R Packages and Their Components and Files
Create an R Markdown Template and Share It
Create an R Package with an R Markdown Template
Wrap-Up
Custom Template Packages and References
Resources for Packages and Forking Repositories
[Lecture Prep] - Code File
Practice
Week 4

Working in Teams and Disseminating Templates and Reports
Week 5 Introduction
Organizing Components - Files, Documents, and Codes
Disseminate Your Files via RPubs and GitHub
Communicating to Your Team on How to Use Your Templates and Projects
More Ways to Disseminate Your Files
Wrap-Up
[Lecture Prep] - Code File
Resources on Dissemination
Practice

Summary of User Reviews

Learn how to create reproducible templates for data analysis in this comprehensive course. Students have praised the clear and concise instruction provided by the instructor, making it easy to follow along with the material.

Key Aspect Users Liked About This Course

Clear and concise instruction

Pros from User Reviews

Great course for learning how to create reproducible templates for data analysis
Instructor provides clear and concise instruction throughout the course
Lots of practical examples to work through
Good pacing and structure to the course
Useful tips and tricks for improving workflow

Cons from User Reviews

Some users found the course material to be too basic
Not enough depth on certain topics
Limited interaction with other students
No opportunity for hands-on practice with real-world data
Some technical issues with the platform

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