- Module 1P - Foundations of Data Science in Python | 5,7,8 Aug 2019
- Topics Covered
- Steps to follow:
- Miscallaneous
- Intro to Jupyter Notebook | Intro to Python | Intro to Pandas - ipynb code
- Practise Session
- Exercise 2 - ipynb code
- Exercise 3 - ipynb code
- Data Basics | Missing Data | Merging and Grouping - ipynb code
- Practise Session
- Exercise 1 - ipynb code
- Exercise 2 - ipynb code
- Exercise 2 - ipynb code
- Matplotlib Basics | Plot from Pandas - ipynb code
- Practise Session
- Exercise 1 - ipynb code
- Exercise 2 - ipynb code
- Data science work flow | Case study: conversion rate analysis - ipynb code
- Mini project 1 - Movie
- Mini project 2 - Student Grade
- Mini project 3 - Camera
** If you don't have a google account, skip to Step 1b **
- Go to https://colab.research.google.com
- Sign in to your google account
- If you are new to google colab notebook, watch this Youtube video - Get started with Google Colaboratory (Coding TensorFlow)
** If the notebook disconnects/ dies often, consider Step 1c. Many students have reported that that connection is not stable**
- Go to https://jupyter.org/try
- Click on "Try Jupyter with Python". This will launch an online jupyter notebook using binder
- If you want to install jupyter notebook into your computer,
- Go to https://www.anaconda.com/distribution/,
- Download
Anaconda
and - Install it
- Click
Start > Anaconda > Jupter Notebook
(in Windows)
- Click
File > New Python 3 Notebook
to create a new.ipynb
file online - Wondering what's a notebook?
- Think of it like a word document where you can write your python code, run and see the outputs, add comments and notes, insert images, etc. in one place.
-
To download entire github repository, click on
Clone or Download > Download Zip
-
To download a specific folder in github repo,
- Copy the folder url as shown below and
- Go to https://minhaskamal.github.io/DownGit/ and Paste the url
- Hit
Download
to download the folder/file