Jump Start with Python¶
This is a collection of notes to jump start in data science with Python
Note
The notes are a joint effort of the instructor and the students in STAT 5255, Fall 2021, through experimental learning.
These notes are built using Jupyter Book 2.0.
I Understand¶
(From Dr. Nicholas Eubank)
Data science is an applied discipline, and so this will be an intensely applied class with lots of hands-on exercises.
To make it possible for us to work through problems together as they arise, we will dedicate most of our class time to completing these exercises in small groups. That means that students will be required to read instructional material before every class so they will be ready to do these exercises. This is what is referred to as ``flipping the classroom.”
In order to make this class organization work, it will be critically important that students do their assigned readings before every class, and as discussed below, this will be reflected in how grades are assigned in this class. Students who do not complete their assigned readings and tutorials before each class should not expect to receive good grades, regardless of performance on project assignments.
We will supplement the in-class exercises with topic presentations.
My Goals (Alphabetical order)¶
Anantharaman, Sreeram¶
Become competent in Python
Successfully complete a project using python
Should be comfortable using python for data analysis
Eada, Surya Teja¶
Be able to tutor or give an intro to python
Successfully complete class project in python
Be comfortable to change my project from R to python
Write a python book with an interactive course (of maybe Applied Statistics)
Hyde, Sydney¶
To become more knowledgeable in Python
Develop more confidence when working with Github
Explore packages within Python for purposes of data visualization and possible interactive component
Complete a project in Python to develop skills which can be applied to the creation of a web application
Min, Zefang¶
Get started with python
Complete a Kaggle project in Python
Contribute to a project and collaborate with others on Github
Survive the class
Xu, Shike¶
Get familiar with Python and Github commands
Develop Python coding skills and try to conduct some real data analysis
Contribute to some tutorial files of this class
Yan, Jun¶
Become competent in Python
Write a (simple) Python package
Write a book manuscript with Jupyter-book
Coach a data science competition on Kaggle
Zhang, Jintao¶
Get to know more knowledge about computer languages
Try to capture the way data scientist build a project by git
Apply data analytic methods in my current study
Task Board¶
Git: Solving conflicts in merging
A tutorial on Jupyter Notebook
YAML (Usage in Rmd and Jupyter books)