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Web Development meets Data Science - Data Science & Backend Workshop

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Description

This repository contains the materials used in the TechLabs workshop 'Data Science & Backend Workshop'. It gives an overview on how Web Development can be combined with Data Science.

Therefore the following topics are covered:

Recommended for tracks Technologies Note
Web Development HTML, JavaScript, CSS, NodeJS Web only project
Web Development & DS/AI HTML, JavaScript, CSS, NodeJs and/or Python Web & DS/AI project
DS/AI Python (and minor HTML & CSS) DS/AI project

frontendbackend.drawio.png

Web Development

Technologies:

  • HTML, CSS, JavaScript & NodeJS

Frontend:
The frontend can be either created in plain HTML, CSS and JavaScript or a framework like React, Angular or Svelte could be used.

Backend:
For the backend a framework like Express.js is recommended as described in the web development track.

Communication between frontend and backend:
REST API, GraphQL, WebSocket or HTTP/2

Web Development & Data Science / Artificial Intelligence

Technologies:

  • HTML, CSS, JavaScript, NodeJS
  • Python

Frontend: The frontend can be either created in plain HTML, CSS and JavaScript or a framework like React, Angular or Svelte could be used.
Plotly can be used for interactive charts and graphs.

Backend:
For the backend a Python based framework like FastAPI is recommended.

Communication between frontend and backend:
REST API

Data Science / Artificial Intelligence

Technologies:

  • Python

Frontend:
CSS only for tuning the UI

Backend:
Use a framework like dash or streamlit

Communication between frontend and backend:
Handled automatically by the framework

Project structure

demo
├── dash
├── express-js
├── fastapi
│   └── frontend
└── streamlit

Appendix

  • Python
    • Web Framework FastAPI
    • Graphing Library Plotly
    • Framework for building ML & data science web apps Dash
    • Framework for build and share data apps Streamlit
  • JavaScript
    • Web Framework Express
    • Graphing Library Plotly
    • HTTP client for brownser and node.js Axios

Additional readings:

Nice tutorials:

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