kishlaykumar1995 / data-x-plaksha

Official Data-X Plaksha repo

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Data-X at Plaksha

Teaching team:

  • Instructor: Alexander Fred-Ojala
  • TA: Joseph Thomas Thachil

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

Resources (same as UC Berkeley class):

Download the material

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

download


▶️ 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/afo/data-x_plaksha

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


📧 Contact

  • Alexander Fred-Ojala: afo @ berkeley edu (LinkedIn)
  • Joseph Thomas Thachil: joseph.thachil @ plaksha.edu.in

📁 About the Course

Today, the world is literally reinventing itself with Data and AI. However, neither leading companies nor the world’s top students have the complete knowledge set to participate in this newly developing world. This course provides the tools and understanding to boost any student’s ability to create the emerging data applications of the future. This bootcamp is suitable for individuals interested in hands-on practical understanding of data science and application opportunities in new ventures, industry project areas, and potential support of research with data technologies.

The Data-X course is a high paced immersion into data and data science principles in a uniquely practical approach. The program contains theory segments, code samples in Python and in Jupyter Notebooks, and a real-life wide ranging project that can be started with guidance for instructors. The course includes a real life code development project.

❤️ Credits

🎓 License

Apache2



Data-X Instructors


About

Official Data-X Plaksha repo

License:Apache License 2.0


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Language:Jupyter Notebook 70.3%Language:HTML 29.6%Language:JavaScript 0.0%Language:Solidity 0.0%Language:Python 0.0%Language:Dockerfile 0.0%Language:Shell 0.0%Language:Procfile 0.0%