This document provides advice on continuing data science and AI education through various options like online courses, academic programs, and professional groups. It acknowledges challenges like a lack of data scientists in Mexico and firms implementing data science projects incorrectly. However, it argues Mexico must become a data science and AI hub to remain economically competitive as automation increases and other countries specialize. Specific recommendations include pursuing a full academic program, building an independent master's with MOOCs, and joining data science communities and groups in Mexico.
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Mexico's Path to Becoming a Data Science and AI Industry Hub
1. Where to go from
here?
1001 ways (or less) to continue diving into DS & AI until you
become a Jedi.
2. Can Mexico become a DS+AI
industry hub?
113K Software Engineers a year.
350 Mathematicians + Actuaries + Physicists + Statisticians.
Distinction between Data Science & Data Engineering not clear.
Lots of great Data Engineers.
Not many Data Scientists.
Lots of Data Engineers trying to be Data Scientists w/o Prob&Stats.
+
3. So? What could go wrong?
Important telecoms firm giving credit to the wrong people.
Relevant internet company missing respiratory illness predictions.
Important software vendor creating a racist, sexually charged
chatbot.
Important internet firm mislabeling 2 african americans as gorillas.
2008 subprime mortgage crisis.
Trump's victory.
4. But firms are to blame too, right?
CTOs drink the "Big Data" kool-aid and call their "buddy" at an IT
Vendor.
Vendor promises unprecedented return if firm buys their "fridges".
Board grants budget out of ignorance. CTO buys boxes.
CTO migrates DWH from RDBMS to Hadoop. For them, this is DS.
Next Q arrives. No ROI. Project canceled. Boxes returned.
CTO no longer able to innovate. SWEngs quit and call themselves DS.
5. Should Mexico become a DS+AI
hub?
Northern border closed to our products & services.
Peak oil.
Rampant corruption.
Weak internal market.
Crappy macroeconomic variables.
Low spending in science & technology. Both private & public.
6. Yes, it must!
We do it wrong, all analytics will be taken to India (as in the 90s).
"Low-cost Country" card no longer works.
Worldwide automation will make our cheap manpower useless.
Either we get on this train, or we see
our country slowly break.
7. How can you help?
Go into a full-fledged academic program.
Go back (briefly) to school.
Build your own MSc with multiple MOOCs.
Join professional groups.
Join communities.
8. Applied Maths @ ITAM, UNAM, IPN
Physics @ UNAM, ITESM
Economics @ ITAM, UNAM
MSc Data Science @ ITAM
MSc Analytical Intelligence @ UAnáhuac
Academic Programs in MX*
+
* Evaluations of 63 candidates for Data Science positions offered at Mexican Stock Exchange, GBM, TERAN/TBWA,
Klustera, Globant, Citi, Konfio, OPI and ConCrédito.
9. Intro to Mathematical Thinking: Stanford + Coursera
Intro to Logic: Stanford + Coursera
Business Analytics: Wharton + Coursera
Data Science Specialization: JHU + Coursera
Machine Learning: Stanford + Coursera
Executive Data Science: JHU + Coursera
DIY MSc: 2-year MOOC Roadmap*
* See ratings on https://www.class-central.com/
10. Sociedad de Científicos de Datos de México
For those wanting to go more into academia.
SocialTIC
Less Data Science, More DataViz: Social Impact, Infoactivism, Govt
Accountability, Data Journalism.
Instituto Internacional de Ciencia de Datos
For those more interested in data governance and "enterprise" DS.
Professional Groups
11. The Data Pub (FB: /thedatapub, TW: @thedatapub)
1050 members. Meetups on the last Thursday of every month.
Present 2 Analytics + DS projects where business comes first, math
comes second, and tech comes third.
Job posting - because some firms still mistake DS for DEs.
Badges - because LinkedIn's endorsement are The Bonfire of Vanities.
Join Communities