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AI@SI Workshop Intro
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Introduction to AI and Machine Learning Pilot Workshop

Smithsonian Institution

July 30, 2021

Please take the pre-workshop survey: https://forms.office.com/r/RfD4KneMqB
if you haven't yet


We will be recording 📹

Only recording instructional portion -- not discussion or breakout rooms


Code of Conduct

We are dedicated to providing a welcoming and supportive environment for all people, regardless of background or identity.

https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html


Code of Conduct

  • Go to Instructors if you feel the Code of Conduct is being violated.
  • There is also a big blue "Report a Code of Conduct Incident" on the workshop website if you feel the Instructors are not handling appropriately.

Instructor/Helper Intros


What is the Carpentries?

https://carpentries.org/

The Carpentries is a global volunteer-driven organization dedicated to teaching computational skills to researchers and anyone who works with data.


Carpentries way of teaching

Normally: Code along, rather than lecturing from PowerPoint, or just demonstrating.


This is a pilot workshop

We intend to give you a top-notch workshop today, but please be patient with us. Your feedback is always important, but it is extra important today.


How to participate

Ask questions with Raised Hand ✋ (under Reactions), or chat in Zoom


How to participate

We will also be asking you to write in a collaborative document.

https://pad.carpentries.org/2021-07-30-intro-ai-pilot


Sign into EtherPad

Go to the workshop EtherPad https://pad.carpentries.org/2021-07-30-intro-ai-pilot now, and "sign in".


Workshop Learning Objectives

Machine Learning "Literacy"


Intro to AI and Machine Learning for GLAM

Overview of terminology and topics.


What is Machine Learning good at?

Types of data that work well with machine learning


Understanding and managing bias in the data science lifecycle

What are the steps of a machine learning process, and how/where can bias get introduced?


Think of how you can apply what you learn today to your own work