I want to hire some people to help me update my websites more frequently, do the maintenance stuff, and to help edit the podcast so I can produce episodes more frequently. I outlined my whole plan here on my Patreon Campaign. You’ll see a new page on this site soon acknowledging supporters, and I’ll update you on the progress. Whether you can give financially, or even if you just share the campaign with your data science friends, you are helping Becoming a Data Scientist podcast, the learning club, Data Sci Guide, Jobs for New Data Scientists, and all of my websites get off the ground! Thank...
I am collecting information about my “audiences” so I can improve my websites, podcast, and also formulate a plan for a Patreon campaign to generate funds for getting help and to free myself up to create more content. Please fill out the survey and share it with your friends and followers on social media! The survey is a little long/detailed, but most of it is optional. I value your opinions! Thank you so much for participating!! Link to the Becoming a Data Scientist Survey
I’m working on the last of my recording and editing for “Episode 0” of the new Becoming A Data Scientist Podcast, which I’m planning to launch tomorrow! I’ve already recorded the interviews for episodes 1-3, which will be airing over the next month or so – so exciting! The guests all had interesting and informative things to share, I believe you’ll like it a lot.
At the end of each podcast episode, I’ll be “assigning” a “Learning Activity” for the Data Science Learning Club.
As data scientists, we are aware that bias exists in the world. We read up on stories about how cognitive biases can affect decision-making. We know that, for instance, a resume with a white-sounding name will receive a different response than the same resume with a black-sounding name, and that writers of performance reviews use different language to describe contributions by women and men in the workplace. We read stories in the news about ageism in healthcare and racism in mortgage lending.
Data scientists are problem solvers at heart, and we love our data and our algorithms that sometimes seem to work like magic, so we may be inclined to try to solve these problems stemming from human bias by turning the decisions over to machines. Most people seem to believe that machines are less biased and more pure in their decision-making – that the data tells the truth, that the machines won’t discriminate.
I have been thinking about doing a “Becoming a Data Scientist” podcast for a long time, at least since April. The podcast would include interviews focused on how people working in various data-science-related jobs got to where they are today (how did they “become a data scientist”?). I’m getting closer to taking the dive and getting it started.
I had an idea today that would take it a step further. Imagine how book clubs work where you pick a book, go off and read it, then gather occasionally to discuss and record your thoughts. Except instead of a book club, it’s a data science learning club!
When I decided that I wanted to become a data scientist, I started following some data scientists on twitter to see what they talk about and what was going on in the “industry”. Then I saw them pointing one another at resources, and answering each other’s questions, and I realized I had only seen the tip of the iceberg of “Data Science Twitter”. That’s when I created a new twitter account.