资源主要来源于”Pycon2018”会议参加者的分享，这是第一篇，后续还会陆续更新关于“大规模数据处理”和“数据可视化”相关的资源。由于微信不能发布外链，在每一项后面增加了链接，可复制链接地址通过浏览器打开。

**●**数据科学学习路线图

How to launch your data science career (with Python) “roadmap” for learning data science from Data School

Link: http://www.dataschool.io/launch-your-data-science-career-with-python/

**●**数据科学学习视频和练习

DataCamp:100+ courses for learning datascience through videos and interactiveexercises, organized by “skilltracks” and “career tracks”

Link: https://www.datacamp.com/

**●**非常受欢迎的“机器学习”课程

Andrew Ng’s Machine Learning course Coursera course, requires an understanding of linearalgebra,programming assignments are in Octave/MATLAB (not Python)

○     Detailedcourse notes from a paststudent

Link: https://www.coursera.org/learn/machine-learning

Link: http://www.holehouse.org/mlclass/

**●**专注于神经网络的“机器学习”博客

AndrejKarpathy’s blog: Machine learning blogwith a focus on neuralnetworks

Link: http://karpathy.github.io/

●基于Python****的“深度学习”课程

PracticalDeep Learning for Coders: Freecourse on deep learning in Python,commonly referred to as “fast.ai”(its URL)

Link: http://course.fast.ai/index.html

●MIT的线性代数课程

Linear algebra: Course from MIT

Link: https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/

●使用Python****进行科学计算

Introduction to Computing using Python course from Georgia Tech

Link: https://www.edx.org/course/introduction-computing-using-python-gtx-cs1301x

**●**微软的人工智能课程

Microsoft Professional Program in AI:9-courseseries

Link:https://www.edx.org/microsoft-professional-program-artificial-intelligence