Getting and Cleaning Data

Go to Course: https://www.coursera.org/learn/data-cleaning

Introduction

### Course Recommendation: Getting and Cleaning Data on Coursera In the modern data-driven world, the ability to gather and preprocess data is essential for anyone looking to make insights from information. That’s why I highly recommend the "Getting and Cleaning Data" course offered by Coursera. This course serves as a comprehensive introduction to the fundamental skills needed to acquire and prepare data for analysis, making it indispensable for aspiring data scientists, analysts, and researchers. #### Overview of the Course "Getting and Cleaning Data" focuses on the vital steps before any analysis can take place—the acquisition and cleaning of data. The course covers various methods for obtaining data, including scraping information from the web, utilizing APIs, retrieving data from databases, and collecting datasets directly from colleagues in diverse formats. A unique emphasis on tidying data sets is particularly valuable, as tidy data helps streamline subsequent analysis processes. The course also explores the essential components of a complete data set comprising raw data, processing instructions, and codebooks, enriching your understanding and approach to data handling. #### Weekly Syllabus Breakdown **Week 1: Finding Data and Reading Different File Types** This initial week sets the stage by introducing students to techniques for identifying potential data sources and methods to ingest different file formats. You will learn to work with CSV, JSON, and other popular formats. This foundation will prove crucial as you progress through the course and encounter more complex data storage scenarios. **Week 2: Common Data Storage Systems and Extraction Tools** In week two, the course delves deeper into the most prevalent data storage systems. You’ll explore how to extract data from various sources, whether they are web pages or databases like MySQL. This knowledge is relevant beyond the classroom, as many roles in data science require proficiency in extracting and managing data from these platforms. **Week 3: Organizing, Merging, and Managing Data** As the course progresses into week three, the focus shifts to the practical tasks of organizing, merging, and managing the collected data. You will learn best practices for structuring your data and the tools that can simplify these processes. This week is crucial for developing skills that lead to efficient data analysis workflows, enabling you to handle real-world datasets with finesse. **Week 4: Text and Date Manipulation in R and Peer Grading** The final week wraps up with valuable lectures on text and date manipulation in R, which are essential skills for cleaning and organizing textual and temporal data. Additionally, this week incorporates peer grading of course projects, fostering a sense of community while allowing you to receive constructive feedback from fellow learners. #### Overall Impression and Recommendation The course materials are well-structured, with engaging video lectures and hands-on exercises that drive home the concepts being taught. The practical skills you acquire through this course are immediately applicable to real-world situations, such as internships or job opportunities in data-related fields. The peer interaction adds an extra layer of learning, enabling you to network with like-minded individuals sharing similar goals. In conclusion, if you are serious about building a career in data science or analytics, enrolling in "Getting and Cleaning Data" on Coursera is a decision you won't regret. The course provides you with the essential skills and knowledge to efficiently source and prepare your data for analysis, setting a strong foundation for your journey in the data landscape. So, take the plunge—your data-driven future awaits!

Syllabus

Week 1

In this first week of the course, we look at finding data and reading different file types.

Welcome to Week 2 of Getting and Cleaning Data! The primary goal is to introduce you to the most common data storage systems and the appropriate tools to extract data from web or from databases like MySQL.

Welcome to Week 3 of Getting and Cleaning Data! This week the lectures will focus on organizing, merging and managing the data you have collected using the lectures from Weeks 1 and 2.

Welcome to Week 4 of Getting and Cleaning Data! This week we finish up with lectures on text and date manipulation in R. In this final week we will also focus on peer grading of Course Projects.