Tools for Strengthening Your Data Literacy

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This self-paced learning guide includes curated contents that suit beginners. It covers the basics of HTML/CSS/JS, No-code/low-code web application development in Airtable, web scraping and data cleaning, SQL, web publishing in WordPress, and introduction to Data Science/Machine Learning.

  1. HTML, CSS, and GitHub
    • Signup with Github and installation of Github Desktop for code sharing and tracking.
    • Installation of Visual Studio Code for web publishing.
    • The HTML document object model (DOM).
    • The Box model, positioning and display properties for page composition.
    • Understanding the use of selectors (e.g. CLASS and ID) to access page elements.
    • Basic rules for combining selectors in styling the page elements.
  2. Application Development Using No-code/Low-code Tools
    • Overview of no-code/low-code application development.
    • Develop database and workflow automation services in Airtable.
    • Understand API support in Airtable.
    • Testing Airtable API with Postman.
    • Workflow automation and API integration.
  3. Introduction to WordPress
    • The Administrator’s dashboard in WordPress.
    • Installation of themes and plugins for extending the functionality of WordPress.
    • The use of Kadence theme for user-friendly web design.
    • Use of the classic and block editors for content preparation and page layout.
    • Use of Kadence blocks for styling HTML DOM elements on the page.
    • Powerful plugins for creating user-defined tables and fields for powerful data import, export, and management.
  4. Introduction to Web Scraping and Data Cleaning
    • Overview of data collection from different sources.
    • Introduction to ParseHub for single-page and multiple-page scraping.
    • The ethical and legal considerations in web scraping.
    • Use of OpenRefine for data cleaning.
    • How to handle inconsistent, incomplete, and incorrect data (e.g. wrong formats and duplicates) in OpenRefine.
  5. Introduction to SQL for Simple Data Analysis
    • What is a relational database?
    • Primary and foreign keys in relational database.
    • Learn SQL using SQLite with DB Browser
    • Filter, sort, and group data using SQL commands
    • One-to-one, one-to-many, and many-to-many relationships in SQL.
  6. Beginning JavaScript I
    • Use of JavaScript to access and control HTML and CSS elements.
    • Introduction to Bootstrap web design framework.
    • Use of Bootstrap for creating navigation bar and form.
    • Introduction to C3 for creating charts and graphs.
    • Introduction to Leaflet for creating maps.
    • Introduction to PapaParse for using Google Sheet to store data and allow access through CSV file sharing.
  7. Beginning JavaScript II
    • Introduction to CRISP-DM and the methodology map as a problem solving framework.
    • Relationships between Data Science, Machine Learning, and Deep Learning.
    • Mathematical basis of Machine Learning and the data pipeline
    • Data Bias and Explainable AI.
    • Introduction to Machine Learning with JavaScript.
Enrolled: 0 students
Duration: 30 hours
Lectures: 12
Video: 30 hours
Level: Beginner
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