Week 1 โ€” Questions (8/22โ€“26)#

The key learning outcomes for this week are:

  • Ask and refine questions that can be answered with data

  • Install and run the software required for the course

  • Write and run basic Python code in a Jupyter notebook

  • Begin to think about the complexity of meaningful questions

This week draws from chapters 1โ€“4 from ๐Ÿ“–ย Python for Data Analysis and chapters 1-2 of ๐Ÿ“–ย Think Like a Data Scientist. If you already know Python, the Python parts should mostly be review.

๐Ÿง Content Overview#

Element Length

๐ŸŽฅย Introduction

11m11s

๐ŸŽฅย Asking Questions

10m35s

๐ŸŽฅย Questioning Questions

8m54s

๐ŸŽฅย Our First Python

9m30s

๐ŸŽฅย Data Types and Operations

19m17s

๐ŸŽฅย Control Structures

6m56s

๐ŸŽฅย Scientific Python

13m20s

This week has 1h20m of video and 0 words of assigned readings. This weekโ€™s videos are available in a Panopto folder.

๐Ÿ“… Deadlines#

This week has the following deadlines:

๐ŸŽฅ Introduction#

This video introduces the course and our learning outcomes for the term.

๐ŸŽฅ Asking Questions#

In this video, I introduce questions in their broader context of using data to advance goals. I also introduce the idea of operationalization, which will be a key concept throughout the class.

Further Reading#

๐ŸŽฅ Questioning Questions#

We make our operationalizations better by questioning them. What do they capture? Who or what do they prioritize?

Note

In this video, I talk about asking what it takes to improve a metric. It would be more precise to ask what would change a metric; whether increasing or decreasing a metric is an improvement depends on the metric and application context. The metric itself does not improve or get worse without that context.

When I re-record this video for a future revision, Iโ€™ll change my language.

๐Ÿ“– Textbook Chapters - Questions#

The first videos of this class go with chapters 1 and 2 of ๐Ÿ“–ย Think Like a Data Scientist.

๐Ÿ‘จโ€๐Ÿซ Tuesday Class#

On Tuesday, we will meet on Zoom and do the following:

  • Introduce the class

  • Start working on defining and clarifying questions

  • Set expectations for the week and semester

โœ… Pre-Class Inventory#

Fill out the pre-class skill inventory and survey by noon on Wednesday.

โœ… Install Software#

Make sure you have installed the course software so you can complete the assignment.

๐Ÿšฉ Week 1 Quiz#

The Week 1 individual quiz (in Canvas) is due at 8am Thursday. It is only over material prior to this point.

You will have 30 minutes from when you start the quiz to complete it. These quizzes are never going to be terribly long; this one is particularly designed to be pretty easy, as an initial quick check and to give you experience with the quiz process.

Tip

I recommend watching the remaining videos before class Thursday as well, but they will not be tested over in the quiz.

๐ŸŽฅ ๐Ÿ““ Our First Python Notebook#

This video shows you how to start Jupyter, create a notebook, and run Python code. It also shows you how to prepare a notebook to submit as an assignment.

Note

I have seen cases where the instructions to export to a PDF do not work correctly in Firefox; they result in a mangled PDF file that does not correctly display charts. If you encounter this problem, I have documented some fixes over in the common problems page.

Resources#

๐Ÿ‘จโ€๐Ÿซ Thursday class#

In class on Thursday, we will:

  • Meet our teams

  • Take the Week 1 team quiz (over the same material as the individual quiz)

  • Debug software installations

  • Activity to dive deeper into defining problems and questions

๐Ÿ“– Textbook Chapters - Python#

The Python material we are working on this week is a subset of the material in chapters 1โ€“4 of the textbook. I donโ€™t expect to you get through all 3 chapters thoroughly this week, and we will be introducing more Python features as we need them throughout the semester. I will note specific chapters and sections relevant to videos in their Resources subsections.

๐ŸŽฅ Data Types and Control Flow#

This video introduces fundamental Python data types and operations, along with variables and basic control flow.

Resources#

๐ŸŽฅ Control Structures#

This video introduces Python control structures and code layout.

๐Ÿ“ƒ Further Python study#

If you would like further study on Python fundamentals, especially if programming in general is new to you, here are some resources:

๐ŸŽฅ Scientific Python#

This video introduces NumPy numpy.ndarray, the fundamental numeric array data structure for scientific computing.

Resources#

  • Textbook Ch. 4

๐Ÿ“ฉ Assignment 0#

Complete and submit Assignment 0 by midnight on August 28.