A huge Thank You! to the awesome students and staff at CodePath for participating in another Alteryx SparkED Workshop.
(If you missed the inaugural session by my friend and colleague @bpatel of the SparkED team, definitely check it out here.
Although much of the hour was spent going through building a predictive model using educational and income data, we touched on a lot more than just the workflow.
A few of the initial talking points we addressed were:
- What is Alteryx? What problem(s) does it solve?
- Is it really that easy to automate the cleaning, transformation, and preparation of data?
Then we jumped into the more advanced notion of predictive modeling:
- How can I use Alteryx to create a predictive model in just minutes?
- What’s going on under the hood? How are these models built?
- How can I tweak, optimize, and build on top of Alteryx models?
On the more existential side, a few ideas we discussed were:
- What does a career in data science/engineering look like?
- How can I leverage my computer science skills in the data field?
- How does a no-code/low-code platform like Alteryx help add to my pre-existing technical skillset?
For those who missed it, or for those who didn’t get enough the first time, you can find a link to the recording here. As well, you can find attached both input data files used during the demo.
Happy solving! 😊