In this series of educational blog posts, we highlight components of data analysis by focusing on 7 topics. Each topic is based on key papers, book chapters or blog posts that we have discussed in class. For each topic, we highlight pitfalls to watch out for and propose solutions when possible, some inspired by the literature and others by class discussion. We invite the readers to share their comments with us to help us improve the posts.

Have you been thinking about getting up to speed with deep learning or applied data ethics? Well, look no further than the latest free courses from fast.ai.

By Juniper Lovato (general conference chair) and Laurent Hébert-Dufresne (conference co-organizer), Vermont Complex Systems Center, University of Vermont

A guide to online scientific conferences — creating a virtual world

It was April of 2020 and in light of COVID-19 we were faced with a difficult decision. Do we go full steam ahead organizing our large international conference (ALife 2020) that we had been planning for the last two years in beautiful Montréal, Québec? Do we move the conference online? Do we cancel it altogether? These decisions are happening all over the world as event organizers weigh the costs and benefits of these three options.

This month we cover the important topic of bias in machine learning. Our selection of tweets includes links to articles, podcasts and tutorials relating to AI ethics.

The Computer Vision and Pattern Recognition conference (CVPR) was held virtually on 14-19 June. As well as invited talks, posters and workshops, there were a number of tutorials on a range of topics. Timnit Gebru and Emily Denton were the organisers of one of the tutorials, which covered fairness, accountability, transparency and ethics in computer vision.

This month we have gathered tweets about some interesting talks, reads, and tutorials relating to AI.

By Brij Mohan Lal Srivastava, Nathalie Vauquier and COMPRISE

This post introduces the concept of speech representation and explains the use of an adversarial approach to train speech-to-text systems. The basics of privacy within the context of speech processing are also considered.

Given the current circumstances worldwide, this month we have selected tweets about some interesting resources, reads, and free online classes that you can take while staying at home. Stay safe!

AI Education Matters is a regular feature in the AI Matters newsletter. Here, Marion Neumann explains the teaching methods she uses to expose students to the ideas and working principles of AI technology.

Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.