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:
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.
Table of Contents
Watch the Pros
Thanks to open course ware there are a ton of awesome university courses online e.g.:
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
- Data Science Overview
- Classification: Precision and Recall
- Confusion Matrix
- UD120 Intro to Machine Learning
- Lesson 2: Naive Bayes
- Lesson 3: Support Vector Machines
So stay tuned!