had a chat with Pi.ai [1]. explained my situation: desire to broaden/improve my skills for work in a way that benefits my non-work life too, ideally
shared my resume, back-and-forthed in the morning, before work. after mowing. had coffee.
tentatively "settled" (non-committal, for now) on (ignoring CFA for various reasons and instead):
1. learning data analysis, starting from scratch. i can use this outside of work for personal research.
2. simultaneously continuing to learn about valuation, financial modeling, etc
3. shifting focus somewhat to datavis, specifically. datavis more closely aligns with my art/design background & interests, but i want a solid data analysis base to build a cute fortress on. no building on sand.
4. maybe i'll circle back to business communication later (not just writing but also design, presenting). business communication closes the loop in a way, blending my existing skillsets with those obtained in steps 1-3. it isn't the end of my trek though. it just marks the end of "lap 1" around the track.
ok. that was my plan. today, i'm starting to explore how to digest all that vague knowledge, and from WHERE??
did today (but will find out if it was a good use of time in the future):
- reading about exploratory data analysis on ibm's website [2]
- sought out structured courses. coursera might have one i can do? i have zero interest in Tableau, Power BI, or other proprietary, non-free solutions, so that's helping me narrow down my options
- spent some time sketching out a datavis project idea
- researched ai training versus inference, especially as it relates to data centers. not related to data analysis, just work. still lots to read on this subject, but i'll get to it tomorrow.
now, it's time for dinner.
university of texas libraries: digital humanities tools & resources
~~~~~~~~~~~~
~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~
🖅 e-brev: gem at wampa dot xyz