Class Schedule

Class Time

Class will be Tuesdays and Thursdays from 1:45pm-3pm (EDT).

Date, Rm

Topic

Do Before Class

In-Class Exercise

Tues, Aug 30

  • Class Introduction

  • Welcome to VS Code

Thurs, Sep 1

  • Command Line Basics

Fri, Sep 2

SOFTWARE INSTALL DAY

A day of trouble shooting install issues

Tues, Sep 6

  • Advanced Command Line

  • Jupyter

  • Packages

Thurs, Sep 8

  • Python Debugger

  • R / Python Differences

  • Packages

Tues, Sep 13

  • Numpy Basics

Thurs, Sep 15

  • Numpy Arrays

Tues, Sep 20

  • Pandas: Series

Thurs, Sep 22

  • Pandas: DataFrames

Tues, Sep 27

  • Pandas: Indices & Missing

Thurs, Sep 29

  • Collaborating using Github

Tues, Oct 4

  • Git and Github 2

Thurs, Oct 6

  • Pandas: Cleaning

  • Tracebacks

Tues, Oct 11 FALL BREAK

Thurs, Oct 13

Tues, Oct 18

  • Grammer of Graphics

  • Intro to Plotting with Altair

Thurs, Oct 20

  • Advanced Plotting

Tues, Oct 25

  • Pandas: Merging

  • Pandas: Loading and saving data

  • JVP pp 149 - 157

  • WM Chapter 6

Thurs, Oct 27

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

Tues, Nov 1

  • Defensive Programming

  • Workflow

  • Backwards Design

  • Getting Help Online

Discuss mid-semester project in class

Thurs, Nov 3

  • Defensive Programming

  • Groupby / Split-Apply-Combine

Tues, Nov 8

  • Pandas: Reshaping

  • Pandas: Categoricals

Thurs, Nov 10

  • Speed and Performance in Python

[finish groupby and reshaping exercises]

Tues, Nov 15

  • Statistics with statsmodels

Thurs, Nov 17

  • Machine Learning with sckikit-learn

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

Tues, Nov 22

No Class

Thurs, Nov 24

THANKSGIVING

Tues, Nov 29

  • Defining Your Own Estimators

  • Regex

Thurs, Dec 1

  • Parallelism

  • Distributed Computing

(Note reading includes a 45 minute video to watch)

Fri, Dec 9th

Final Project Report and Presentation Due

Reminders: