DiegoTurri.com

HTML

Projects that include this skill

Medical center front view on white background. Hospital building vector design.

Database Design of a Hospital Chain

Brief Description Given a text from Subject matter experts, I extracted insights to understand the requirements of the database. I created the E-R schema, restructured it, and then created the corresponding relational model. I made the SQL instructions to create tables and relationships between them. I used PostgreSQL as a database and linked it to…

Web Application

Description: Recipes discovery The application uses theMealDB API to retrieve information about different recipes and allows users to discover them , save them as favourites, and review them. Technical details: Homepage: Product page: Profile: Try my code yourself Grade obtained: 100% (30/30) Client: University of Milan Project Duration: 1 month Place: Remote Language: English

Definition

HTML, or HyperText Markup Language, is the standard markup language for creating web pages. It is used to structure and format content on a web page, such as text, images, and links. HTML is a relatively simple language to learn, and it is a valuable skill for data scientists to have.

There are a number of reasons why HTML is useful in data science:

  • Data visualization: HTML can be used to create data visualizations, such as charts and graphs. This can be useful for communicating data findings to others or for exploring data yourself.
  • Web scraping: HTML can be used to scrape data from websites. This can be useful for collecting data for analysis or for building machine learning models.
  • Building web applications: HTML can be used to build web applications that can be used to collect, analyze, and visualize data. This can be useful for creating tools for yourself or for sharing with others.

Here are some examples of how HTML can be used in data science:

  • A data scientist could use HTML to create a web application that allows users to upload data and generate interactive charts and graphs.
  • A data scientist could use HTML to scrape data from a website that publishes financial data and then use that data to build a machine learning model to predict stock prices.
  • A data scientist could use HTML to create a web application that allows users to explore a large dataset of gene expression data.

Overall, HTML is a valuable skill for data scientists to have. It can be used for a variety of tasks, such as data visualization, web scraping, and building web applications.

Here are some tips for learning HTML:

  • Start with the basics: Learn the basic HTML elements and attributes. You can find many tutorials and articles online that can teach you the basics of HTML.
  • Practice regularly: The best way to learn HTML is by practicing regularly. Try to create some simple web pages using HTML.
  • Use a code editor: A code editor can help you to write and edit HTML code more easily. There are many free and open source code editors available, such as Sublime Text and Visual Studio Code.
  • Get help from others: There are many online forums and communities where you can get help from other HTML developers. If you are stuck, don’t be afraid to ask for help.

By following these tips, you can learn HTML and become a more valuable data scientist.