Skip to content

Latest commit

 

History

History
133 lines (105 loc) · 7.13 KB

README.md

File metadata and controls

133 lines (105 loc) · 7.13 KB
Raw

🤖 Head Start to Data Science

Banner Image

< Head Start to Data Science with CSI SFIT/>

Table of Contents

  1. 🥰 Details of the workshop
  2. 🤓 Prep for Prerequisites
  3. 🤩 Workshop Resources

1. Details of the workshop

Whether you’re just learning to code or you’re a machine learning coder already, this workshop will help you develop your skills and advance your projects. Your first-class ticket to the most exciting career in data analysis!

This Virtual Crash Course features a series of lessons, real-world case studies, live coding and hands-on practice exercises carefully curated as a bootcamp for Data Science Beginners.

Leave your regressions behind 🙈 and Let's #makeIThappen with Data Science ⚡

Contents of the Workshop:

☑️ Domains in Data Science

☑️ Tools to train ML models

☑️ Numpy

☑️ Pandas

☑️ Matplotlib

☑️ Seaborn

☑️ Scikit-learn

☑️ 3 Hands-on Projects

Workshop Speakers:

Image
Kaif Kohari
Joint Tech Head'20
 Shardul Shroff Image
Shardul Shroff
Tech Exec'20
 Varun Patkar Image
Varun Patkar
Tech Exec'20

2. Prep for Prerequisites

If you don't know Python or are just a beginner, we recommend viewing these 💗 FREE 💗 resources:

3. Workshop Resources

👉 Google Colab Notebook Links:

  1. Numpy Colab Notebook
  2. Pandas Colab Notebook
  3. Numpy Pandas Takeaway/Homework Notebook
  4. Matplotlib
    1. Matplotlib Concepts Colab Notebook
    2. Matplotlib Exercise Colab Notebook
    3. Matplotlib Exercise Solutions Colab Notebook
  5. Seaborn
    1. Seaborn Concepts Colab Notebook
    2. Seaborn Exercise Colab Notebook
    3. Seaborn Exercise Solutions Colab Notebook
  6. Projects
    1. Linear Regression Notebook (1000 companies)
    2. Logistic Regression Notebook (Breast Cancer detection)
    3. K-Means Clustering Notebook

👉 Additional Resources:

How to Contribute

  1. Clone repo and create a new branch: $ git checkout https://github.com/CSI-SFIT/Head-Start-to-Data-Science.
  2. Make changes and test.
  3. Submit Pull Request with comprehensive description of changes.

Acknowledgements

CSI SFIT Tech Team 2020 - 2021 :


csi_logo