My personal road map for learning data science in 2018

I got confused by all the buzzwords: data science, machine learning, deep learning, neural nets, artificial intelligence, big data, and so on and so on.

As an engineer I like to put some structure to the chaos. Inspired by Roadmap: How to Learn Machine Learning in 6 Months and Tetiana Ivanova – How to become a Data Scientist in 6 months a hacker’s approach to career planning I build my own learning road map for this year:

The Plan

So 2018 will be all about Data Science. Hearing about the Personal Knowledge Mastery concept at SWEC17 I am going to tackle the learning process on different levels.

Watch the Pros

Thanks to open course ware there are a ton of awesome university courses online e.g.:

MIT 6.0002 Introduction to Computational Thinking and Data Science

All videos related to data science I come across Youtube will be added to my Data Science Youtube Playlist

Learn the tools

There is already a whole bunch of tools we can consider belonging to a standard data science stack. Because my main language is Python the focus is of course on mostly python modules.

Finishing Udacity / Udemy courses

To brush up my python skills and my knowledge of basic computer science I will finish some already started online courses:

Reading data science books

To get a broad overview I bought two books on DS / ML

  • [ ] Data Science from Scratch
  • [ ] Hands on Machine Learning

Do Exercises on Kaggle

[x] Create Account at Kaggle

[ ] Do first exercise

[ ] Participate in a contest

Visit Meetups about Data Science

[ ] Visit Big Data Meetup Events

Add some Peer Pressure

My brother in law and I teemed up and build a Whatsapp learn & exchange group. We are currently four members.

Write Blog Articles

I will try to incorporate some of the stuff I’ve learned into blog articles.

I already did Bayes’ Theorem Part 1

So stay tuned!

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