How to get started with Data Science?
I started learning Python a few weeks back with only a little background in R. With Codeacademy, Coursera, ebooks, Stock Overflow, and github, I was able to start hacking interesting question within a few weeks. This open source eduction is incredible!! You can do it too!
1. Python
Online tools:
A. General:
- Codeacademy: provides an interactive platform to learn first commands in Python
- Google's Python Class: a great way to get your feet wet with some exercises
- Python: Python has a great documentation section
- Ask questions - search for answers: http://stackoverflow.com/
B. Info on Modules:
- Pandas - Wes McKinney's video: worth watching!
- Pandas in 10 minutes: Great way to get started with Pandas
- Matplotlib
- Cartopy: Used for creation of maps
- Django: How to tango with Django
Books:
- Learning Python 5th edition
- Python for Data Analysis
- Python Pocket Reference
- Pandas: powerful Python analysis toolkit
2. Databases/ MySQL
- SQLZ tutorial: fun and easy to follow
- Zetcode: How to get started
- Stanford University's online Database course
3. Machine Learning
- Coursera: Course by Andrew Ng (Stanford University)
4. Statistics
(a few options for beginners)
- Udacity
- Khan Academy
- Coursera: Statistics one
5. Data Science Courses and Fellowship Programs:
- Coursera: Data Science Course
- Overview on Data Science Bootcamp Programs (!!!)
6. GitHub
- git - the simple guide
- github.com
- try.github
7. Learning by Doing
(attack a mini challenge)
- Kaggle
- Leada
Other interesting reads:
- What is a data scientist?
- Insight Fellow - how to prepare!
- Harvard Magazine: "Why big data is a big deal"
TIPS:
1. Find a local Data Science Meetup
2. Work on a side project
Photo source: http://school.discoveryeducation.com/clipart/clip/firstaidkit4c.html
Online tools:
A. General:
- Codeacademy: provides an interactive platform to learn first commands in Python
- Google's Python Class: a great way to get your feet wet with some exercises
- Python: Python has a great documentation section
- Ask questions - search for answers: http://stackoverflow.com/
B. Info on Modules:
- Pandas - Wes McKinney's video: worth watching!
- Pandas in 10 minutes: Great way to get started with Pandas
- Matplotlib
- Cartopy: Used for creation of maps
- Django: How to tango with Django
Books:
- Learning Python 5th edition
- Python for Data Analysis
- Python Pocket Reference
- Pandas: powerful Python analysis toolkit
2. Databases/ MySQL
- SQLZ tutorial: fun and easy to follow
- Zetcode: How to get started
- Stanford University's online Database course
3. Machine Learning
- Coursera: Course by Andrew Ng (Stanford University)
4. Statistics
(a few options for beginners)
- Udacity
- Khan Academy
- Coursera: Statistics one
5. Data Science Courses and Fellowship Programs:
- Coursera: Data Science Course
- Overview on Data Science Bootcamp Programs (!!!)
6. GitHub
- git - the simple guide
- github.com
- try.github
7. Learning by Doing
(attack a mini challenge)
- Kaggle
- Leada
Other interesting reads:
- What is a data scientist?
- Insight Fellow - how to prepare!
- Harvard Magazine: "Why big data is a big deal"
TIPS:
1. Find a local Data Science Meetup
2. Work on a side project
Photo source: http://school.discoveryeducation.com/clipart/clip/firstaidkit4c.html