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Computational Audiology Discussion Group | Fall 2021

October 31 - November 28

Free

Moderator:

Stephanie Fowler, PhD, AuD, ABA-C
Director of Clinical Education, AuD Program
Department of Speech, Language, and Hearing Sciences
The University of Texas at Dallas
anie.fowler@gmail.com

Overview:

In conjunction with the free online video series AI For Everyone by Andrew Ng of Stanford (available here on Coursera), interested CAN members can join a discussion group on that topic on a set day within the Slack #readinggroup channel. These discussions are intended to clarify topics learned during that week’s lesson, as well as come up with applicable ways to consider these topics within your own lab or across labs and specialties.

Process:

  1. Sign up for Coursera and “enroll” in the AI for Everyone course.
  2. Join the #readinggroup channel in the Computational Audiology Network Slack.
  3. On your own time during the week listed in the first column below, watch the selected videos from the lesson in the third column. Feel free to enter your questions early into the #readinggroup channel.
  4. On the date listed for discussion (Sundays in November at 10a Central Time [Chicago, USA]), log in to the Slack #readinggroup channel, and post at least one question and respond to at least two questions. I will contribute questions and moderate the conversations if they start to stall for the 10a-11a hour, but feel free use this forum to have your discussions even outside these hours.

Schedule:

Week:Discussion Date:Topics and Materials:
Oct 31 – Nov 6Nov 7

10:00am – 11:00am CT

What is AI? [est. time 1h 48m]

  • Week 1 Introduction
  • Machine Learning
  • What is data?
  • The terminology of AI
  • What makes an AI company?
  • What machine learning can and cannot do
  • More examples of what machine learning can and cannot do
  • Non-technical explanation of deep learning (Part 1, optional)
  • Non-technical explanation of deep learning (Part 2, optional)
Nov 6-13Nov 14

10:00am – 11:00am CT

Building AI Projects [est. time 1h 21m]

  • Week 2 Introduction
  • Workflow of a machine learning project
  • Workflow of a data science project
  • Every job function needs to learn how to use data
  • How to choose an AI project (Part 1)
  • How to choose an AI project (Part 2)
  • Working with an AI team
  • Technical tools for AI teams (optional)
Nov 14-20Nov 21

10:00am – 11:00am CT

Building AI In Your Company [est. time 2h]

  • Week 3 Introduction
  • Case study: Smart speaker
  • Case study: Self-driving car
  • Example roles of an AI team
  • AI Transformation Playbook (Part 1)
  • AI Transformation Playbook (Part 2)
  • AI pitfalls to avoid
  • Taking your first step in AI
  • Survey of major AI application areas (optional)
  • Survey of major AI techniques (optional)
Nov 21-27Nov 28

10:00am – 11:00am CT

AI and Society [est. time 1h 29m]

  • Week 4 Introduction
  • A realistic view of AI
  • Discrimination/Bias
  • Adversarial attacks on AI
  • Adverse uses of AI
  • AI and developing economies
  • AI and jobs
  • Conclusion

 

 

Details

Start:
October 31
End:
November 28
Cost:
Free