Data Science with R - Capstone Project

Go to Course: https://www.coursera.org/learn/data-science-with-r-capstone-project

Introduction

**Course Review: Data Science with R - Capstone Project** If you're looking to solidify your data science skills and gain practical experience, the "Data Science with R - Capstone Project" course on Coursera is an excellent choice. Offered as part of the IBM Data Science with R Specialization, this course is designed to be the culminating experience where you can apply the knowledge you've gained throughout the specialization. ### Course Overview The capstone project places you in the role of a data scientist who has just joined an organization facing a real-world challenge. This immersive experience includes key tasks such as data collection, analysis, hypothesis testing, visualization, and modeling. The structure of the course ensures that you navigate through all the crucial stages of a data science project, providing you with valuable insights into each step of the process. ### Syllabus Breakdown #### Module 1: Capstone Overview and Data Collection The course kicks off by setting the stage for what is to follow. You will explore the objectives of the capstone project and how to collect the necessary data. This module emphasizes the importance of data sourcing and its direct impact on the quality of your analysis. #### Module 2: Data Wrangling Once you have your data, it’s crucial to prepare it for analysis. In this module, you will learn various data wrangling techniques, ensuring that the data is clean, organized, and ready for exploration. Mastery of data wrangling is essential for any data scientist, and this module sets a solid foundation. #### Module 3: Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2 In this exciting phase, you'll employ SQL querying alongside R's Tidyverse and ggplot2 for exploratory data analysis (EDA). EDA is a critical stage where you gain insights into your data, identify patterns, and uncover potential trends. With hands-on labs, you'll have the opportunity to manipulate your datasets, visualize findings, and prepare for deeper analysis. #### Module 4: Predictive Analysis Building upon your findings from EDA, this module introduces predictive analytics techniques. Here, you'll learn how to use historical data to make informed predictions about future events. This is where you begin to leverage statistical models and machine learning algorithms, enhancing your data science toolkit. #### Module 5: Building an R Shiny Dashboard App One of the standout features of this course is its practical approach to building an interactive R Shiny dashboard. You’ll learn how to present your data and insights visually, making the information more accessible to stakeholders. This skill is invaluable, as effective communication of data-driven insights can greatly influence business decisions. #### Module 6: Present Your Data-Driven Insights The final module pulls everything together, emphasizing the importance of storytelling with data. You’ll learn how to communicate your findings, making complex analyses understandable and actionable for a non-technical audience. This module encapsulates the entire journey of a data scientist, from data collection all the way to delivering strategic insights. ### Conclusion and Recommendations The "Data Science with R - Capstone Project" course is ideal for individuals who want to transition from theoretical knowledge to practical experience in data science. Its well-structured modules, hands-on labs, and real-world applications allow you to develop a comprehensive skill set that prepares you for a career in data science. I highly recommend this course for learners who have completed the foundational content of the IBM Data Science with R Specialization or the IBM Data Analytics with Excel and R Professional Certificate. Not only will you enhance your technical skills, but you will also gain confidence in your ability to handle real-life data challenges. Whether you are looking to break into the data science field or elevate your existing skills, this capstone project is a fantastic opportunity to showcase what you've learned and launch your career with a solid portfolio of work. Dive in, and transform your data science journey into a successful narrative!

Syllabus

Module 1 - Capstone Overview and Data Collection

At this stage of the Capstone Project, you have gained some valuable working knowledge of data collection and data wrangling. You have also learned a lot about SQL querying and visualization. Congratulations! Now it's time to apply some of your new knowledge and learn about Exploratory Data Analysis (EDA) techniques, again through practice. You can use the datasets you wrangled in the previous Module. However, if you had any issues completing the wrangling, no worries - we have prepared some clean datasets for you to use. You will be asked to complete three labs: