Remember our short discussion on Programming Languages in the Fintech class? As languages evolve, developers’ preferences do too. Here is a survey from Stack Overflow. Read on. Please send me your views to my Stanford ID, especially on Rust which we didn’t discuss.
In this course I plan to cover items 1 through 5. I’m flexible with the level of participation from students in programming exercises in step 5 (ML). Depending on backgrounds and goals, students may choose not to program (why learn programming if you can hire a developer for 10$/Hr?) or actively program in R and/or Python.
0) How much ‘Fin’ and how much ‘Tech’?
1) How banks’ reluctance to innovate/adopt led to Fintech. Banks! You can’t bank on them.
2) The ultra-personalisation of financial services through technology – the driver behind Fintech
3) Case Studies – Peer-to-peer lending, Crypto-currencies, Robo-advisers, online-only digital banks
4) My Money Karma
5) Machine Learning using R (or Python)
Please contact me at my Stanford email ID.
This video is for IIM students who had questions on how to visually represent the strengths of in-centrality and out-centrality in social networks. Don’t focus too much on coding in R. Pay attention to centralities instead. As usual, if you have questions, please contact me through my Stanford email id.