Class Schedule

Class Time

Class will be Tuesdays and Thursdays from 1:25pm-2:40pm (EDT).

Date, Rm

Topic

Do Before Class

In-Class Exercise

Tues, Aug 29

  • Class Introduction

  • Welcome to VS Code

Thurs, Aug 31

  • Command Line Basics

Fri, Sep 1

SOFTWARE INSTALL DAY

A day of trouble shooting install issues

Tues, Sep 5

  • Advanced Command Line

  • Git

  • Packages

Thurs, Sep 7

  • Git Continued

  • Jupyter

Tues, Sep 12

  • Python Debugger

  • R / Python Differences

  • Packages

Thurs, Sep 14

  • Numpy Basics

Tues, Sep 19

  • Numpy Arrays

More Numpy Concepts:

Matrices:

ND Arrays:

Thurs, Sep 21

  • Pandas: Series

Tues, Sep 26

  • Pandas: DataFrames

Thurs, Sep 28

  • Pandas: Indices & Missing

Tues, Oct 3

  • Pandas: Cleaning

  • Tracebacks

Thurs, Oct 5

  • Grammer of Graphics

  • Intro to Plotting with Altair

Tues, Oct 10

  • Advanced Plotting

Thurs, Oct 12

FALL BREAK

Tues, Oct 17

FALL BREAK

Thurs, Oct 19

  • Pandas: Merging

  • Pandas: Loading and saving data

  • JVP pp 149 - 157

  • WM Chapter 6

Tues, Oct 24

  • Big Data: What is it, how do I work with it?

Thurs, Oct 26

  • Defensive Programming

  • Workflow

  • Backwards Design

  • Getting Help Online

Discuss mid-semester project in class

Tues, Oct 31

  • Defensive Programming

  • Groupby / Split-Apply-Combine

Thurs, Nov 2

  • Pandas: Reshaping

  • Pandas: Categoricals

Tues, Nov 7

  • Speed and Performance in Python

[finish groupby and reshaping exercises]

Thurs, Nov 9

  • Statistics with statsmodels

Tues, Nov 14

  • Machine Learning with sckikit-learn

  • JVP Chapter 5 up to “Hyperparameters and Model Validation” Section (pp 331 - 359)

Thurs, Nov 16

Tues, Nov 21

No Class

Thurs, Nov 23

THANKSGIVING

Tues, Nov 28

  • Defining Your Own Estimators

  • Regex

Thurs, Nov 30

  • Parallelism

  • Distributed Computing

(Note reading includes a 45 minute video to watch) Optional: - Setting Up Cloud Cluster

Fri, Dec 8

Final Project Report and Presentation Due