Merge pull request #162 from pdxrconf/correct_lydia_times

correct lydia reported times

content/speakers/speaker_info_2024/regular/lydia_gibson/index.md

@@ -4,7 +4,7 @@ url: "2024/regular/lydia_gibson"
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 ### Learning Together at the Data Science Learning Community
-Regular talk, 1:15-1:30
+Regular talk, 3:15-3:30
 
 Whether we are seeking our first job as a data professional or continuing a journey years in the making, we must all constantly learn new data programming skills to keep up with a rapidly changing world. Bootcamps and courses are often expensive, and it can be difficult to maintain the motivation necessary to learn skills on our own. The Data Science Learning Community is here to help. You may have heard of us previously as the R4DS Online Learning Community. We started with a handful of nontraditional learners reading R for Data Science together, but we’re about much more than any single book. For more than four years, we’ve organized weekly book clubs to help data science learners and practitioners read books such as R for Data Science, Advanced R, and Mastering Shiny. In contrast with other online book clubs, our safe, nurturing, small-group cohorts finish reading their books cover-to-cover. Come learn the tips and tricks that lead to the success of our clubs. In addition to our book clubs, the thousands of members of our diverse community also support one another by asking and answering programming questions in our Slack help channels. I’ll discuss how we keep those channels friendly and inclusive, and how we work to ensure that we answer every question. I’ll also show you where you can find over 600 curated datasets to practice those data skills. We post new datasets weekly as part of our #TidyTuesday social data project, and invite learners to practice their data visualization and machine learning skills, and share their learning back to the community. Come discover how you can help us make sure all of this remains absolutely free for everyone who wants to learn, worldwide. I encourage anyone who would like to gain and maintain expertise in data science techniques to attend my talk.
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