/Learning-with-Jelly-Data-Analyst

Primary LanguageJupyter Notebook

Introduction to Data Analytics Track (YouTube Playlist)

Overview

Hello everyone and welcome to Learning with Jelly! This repositiory contains all the PowerPoint Presentations and Coding Notebooks for the Data Analytics Track on my Youtube channel. This track aims to teach foundational skills needed to dive into the world of Data Analytics and eventually Data Science. The best way to follow along with the tutorials is to Fork this repo (so you have a copy of it on your own GitHub account), clone it down from your own account, fill in the notebooks, then push the changes back up to YOUR repository. The next section will take you through these steps

Steps to Connect to the Repo

These steps you should only need to do at set up:

  1. FORK this repository, creating copy on your own GitHub account

In order to fork, look to the upper right of this page, between 'Watch' and 'Star'. From that drop down you should see an option to create a new fork.

That will open a new page, and you'll be given an option to select a new owner for the fork. Select your own account. Ignore the other options.

  1. CLONE your fork to your local computer

To do this, navigate in your terminal to an appropriate folder. I recommend you have an overall 'Data_Analytics' folder either in your documents or on your desktop. Once you're in the right place, you'll need to input the following command, replacing '[yourusername]' with your Github account:

git clone https://github.com/[yourusername]/Learning-with-Jelly-Data-Analyst.git;

  1. If you want to push your changes from your local to the forked version of the repo use these steps:

    git add [filename]

    git commit -m 'message here'

    git push

Modules Covered in this Track

  • Module 1: Intro to Data Analytics
  • Module 2: Python Data Types
  • Module 3: Iterating through Data in Python (Lists)
  • Module 4: Iterating through Data in Python (Dictionaries) - on different platform (TBA)
  • Module 5: Python Packages for Data Analysis - on different platform (TBA)
  • Module 6: Data Manipulation with Pandas - on different platform (TBA)
  • Module 7: Statistics - on different platform (TBA)
  • Module 8: Data Visualization - on different platform (TBA)
  • Module 9: SQL - on different platform (TBA)