Mastering Software Development in R Capstone

Johns Hopkins University via Coursera

Go to Course: https://www.coursera.org/learn/r-capstone

Introduction

# Course Review: Mastering Software Development in R Capstone on Coursera If you are looking to solidify your expertise in R programming while simultaneously contributing to an engaging and practical project, the "Mastering Software Development in R Capstone" course on Coursera is an opportunity you shouldn't miss. This course acts as a culmination of the skills you have acquired throughout the specialization, making it a vital step for anyone serious about a career in data science or software development in R. ## Overview The Mastering Software Development in R Capstone focuses on integrating your learning by allowing you to build a software package designed to work with the **NOAA Significant Earthquakes dataset**. The hands-on project involves several key components of software development in R, ensuring that you not only understand how to analyze the data but also how to create a functional, sharable package. ## Syllabus Breakdown ### 1. Obtain and Clean the Data The course starts with the critical phase of obtaining and cleaning the dataset. Here, learners are introduced to the importance of robust data acquisition techniques and methods for data cleaning—skills that are fundamental for any data analyst or scientist. This portion of the capstone emphasizes the necessity of effective data preparation, setting the stage for analysis and visualization. ### 2. Building Geoms Next, participants will work on converting raw data into insightful visualizations. You will learn to build geoms that represent when earthquakes occurred in various countries, their magnitude, and the toll on human life. This section highlights the art of transforming data into informative graphics, demonstrating the power of R in exploratory data analysis. ### 3. Building a Leaflet Map One of the project highlights is the creation of a Leaflet map to display and annotate earthquake epicenters. This is a particularly exciting segment, as mapping data geographically often leads to powerful insights. You’ll not only learn the technical skills to create interactive maps but also understand the contextual implications of the data visualized. ### 4. Documentation and Packaging Documentation is often an overlooked aspect of software development, yet it's critical for the usability and maintainability of your code. The course places a strong emphasis on this step, ensuring that learners come out of the course with the knowledge to create comprehensive documentation for their software packages. Proper documentation will enhance collaboration and future use of your work. ### 5. Deployment As you near the project's completion, you'll experience the thrill of deploying your package to GitHub, marking the transition from development to sharing your work with the world. This step reinforces the importance of open-source contributions and showcases your ability to manage version control, a crucial skill in the software industry. ### 6. Final Assessment The capstone culminates in a final evaluation where you submit your deployed package and assess your peers' work. This not only tests your understanding of the course material but also enhances your critical thinking and feedback skills—both of which are essential in professional environments. ## Recommendation I highly recommend the "Mastering Software Development in R Capstone" course for anyone looking to enhance their R programming skills while undertaking a meaningful and collaborative project. The course effectively merges theoretical knowledge with practical application, allowing you to build a portfolio-worthy project. Moreover, the skills you develop in data cleaning, visualization, documentation, and deployment are invaluable in today's data-driven job market. Upon completion, you will feel confident not only in your technical abilities but also in your capability to contribute to real-world projects and collaborate with peers. Overall, whether you are a student, an aspiring data scientist, or a current professional seeking to upskill, this course will serve as a comprehensive and rewarding experience that equips you with practical skills and a solid foundation for your future endeavors in software development.

Syllabus

Obtain and Clean the Data

The overall goal of the capstone project is to integrate the skills you have developed over the courses in this Specialization and to build a software package that can be used to work with the NOAA Significant Earthquakes dataset.

Building Geoms

Show us when earthquakes occurred in different countries, their magnitude, and their toll on human life.

Building a Leaflet Map

Show and annotate the earthquake epicenters.

Documentation and Packaging

Documentation is one of the most important and most commonly overlooked steps when writing software, but you're not going to let that happen in your project.

Deployment

The moment of truth. It's time to push your package to GitHub.

Final Assessment

It's time to submit your deployed package for evaluation and to evaluate the work of a few of your classmates.