Tools for Strengthening Your Data Literacy

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.
8. Basic Python Programming I & II
   • Introduction to Python Programming using Jupyter Notebook.
   • Data types and basic mathematical and logical operations in Python.
   • Basic data structures using Python list and dictionary.
   • Introduction to Python functions, classes, and modules.
   • Using Python libraries such as Pandas and Matplotlib for data representation and data visualization.
9. Basic Python Web Programming in Flask I & II
   • Implement web information architecture (IA) by using content management system (CMS) and search engine optimization (SEO).
   • Perform SEO to improve IA by using Google Keyword Planner and Search Console.
   • Implement CMS functions in Python Flask using a MVC (model, view, controller) framework.
   • Perform database CRUD operatons (create, retrieve, update, delete) using the FlaskSQLAlchemy library.
   • Registration and login authentication using Flask-login and JWT libraries.