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Data-X Instructors

INDENG 135 / 235, Applied Data Science with Venture Applications: Data-X

Link to course website & syllabus

Teaching Team Fall 2021:

  • Faculty: Ikhlaq Sidhu and Derek S. Chan
  • GSIs: Mahan Tajrobehkar and Ruiqi Guo

This is the official Github repository for the Data-X class at UC Berkeley

Cours

Course Website:

Download the material

To download this Github repository just press the green Clone or Download button to the top right.

download


Viewing the material

You can view all material in this repository through Binder: Link

Here is a compiled list of resources which with you can view the material. Using these resources may involve creating an account. To view the material through a virtual environment, check out the resources below:

  • Repl.it offers an in-browser IDE where you can copy and paste Python code to try out. You can either download code onto the site or load code from your Github repo.
  • PythonAnywhere is a place where you can host, run and code Python in the cloud. You may pay extra to load a Jupyter Notebook environment.
  • Binder turns a Git repo into a collection of interactive notebooks. After forking the repo, you can copy and paste the URL, and Binder will create a reusable link which allows you to access the material in an interactive environment on your browser.

▶️ Usage

To download the material to your computer please Install git and use the Terminal / Command Prompt to clone the repository.

git clone https://github.com/ikhlaqsidhu/data-x.git

Every time the repository is updated, to get the most recent version, cd to the cloned data-x folder and run:

git pull

For more information about Version Control, git, and Github please read this excellent guide: Introduction to git and Github

❤️ Credits

List of Dependencies:

✅ Past contributors

  • Alexander Fred-Ojala: afo @ berkeley edu (LinkedIn)
  • Ming-Yen Kao, Johann Schleier-Smith, Shunan Jiang (Fall 2020 GSIs)
  • And many more people!

🎓 License

Apache2



Data-X Instructors


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  • Jupyter Notebook 76.1%
  • HTML 17.1%
  • Python 6.8%
  • JavaScript 0.0%
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