Tetiana Ivanova: How to become a Data Scientist in 6 Months, a Hacker's Approach to Career Planning
PyData London 2016

This talk outlines my journey from complete novice to machine learning practitioner. It started in November 2015 when I left my job as a project manager, and by April 2016 I was hired as a Data Scientist by a startup developing bleeding edge deep learning algorithms for medical imagery processing.

SHORT INTRO
Who I am, my background and a short summary of my story. Here I will list the steps I personally took to achieve the goal I had.

HOW DID I DO IT?
Why I chose a “hacky” way to enter this career path. The first mover advantage, why getting a degree doesn’t always improve your career prospects. Possibly a rant on the signaling function of formal education and how that is rarely aligned with a relevant practical skill set. Some stats to back it up (best career success predictors). Examples of hacking bureaucracies/social hierarchies from my experience and elsewhere.
List of things not to do and common cognitive pitfalls.
Networking for nerds - how to do it right.
Time management for chronic procrastinators - how to plan a self-guided project. Some notes on psychology of time discounting and need for external reinforcement, with autobiographical examples.

CONCLUSION
You don’t need a Ph.D. or even a master's to do machine learning. On taking calculated risks and especially calculated exits from one’s comfort zone. Some notes on soul searching and how to choose a career that is also a passion. Reading list.

Slides available here: https://www.slideshare.net/TetianaIva...

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0:00 Introduction
4:56 Higher education
13:02 Things not to do
17:55 What did I do in the end?
21:51 Time discounting and willpower
26:27 Time management techniques
31:37 Networking
37:18 Resources for Data Science transition
44:34 Don’t get started
45:51 Q&A

S/o to https://github.com/anzelpwj for the video timestamps!

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