1. Coursera

• 吴恩达 Coursera Machine Learning
  无需翻墙，可购买证书，不买也能听
• Coursera的其他课程现在好像都要收费了，有free trial，也可以申请financial aid

2. edX

• edX 目前不收费，如果需要购买证书也需要付费，一般在400-600RMB不等
• edX上不仅有大学出品的课程，还有Microsoft等公司出品的课程
• MIT Introduction to computational thinking and data science
  虽然名字里有data science, 归类是computer science
  课程在Youtube上也有
  每周需要15hours
  部分课程简介：
  This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. You will spend a considerable amount of time writing programs to implement the concepts covered in the course.
  Topics covered include:
  Advanced programming in Python 3
  Knapsack problem, Graphs and graph optimization
  Dynamic programming
  Plotting with the pylab package
  Random walks
  Probability, Distributions
  Monte Carlo simulations
  Curve fitting
  Statistical fallacies
  总的来说，这个课程对python要求较高，如果不达标，请补前课
• MIT Introduction to Computer Science and Programming Using Python
  也就是上门课的前一门，教如何使用python, 也涉及部分算法和数据结构，同样是每周15hours，同样在Youtube上有
• 如果上面两门太难了：
  Microsoft Introduction to Python for Data Science
  课程的syllabus如下：
  Explore Python language fundamentals, including basic syntax, variables, and types
  Create and manipulate regular Python lists
  Use functions and import packages
  Build Numpy arrays, and perform interesting calculations
  Create and customize plots on real data
  Supercharge your scripts with control flow, and get to know the Pandas DataFrame
  总的来说，就是教你用python处理数据
  证书比较贵，要657CNY（上面两个是300多/each）
• Columbia Statistical Thinking for Data Science and Analytics
  课程内容：
  Data collection, analysis and inference
  Data classification to identify key traits and customers
  Conditional Probability-How to judge the probability of an event, based on certain conditions
  How to use Bayesian modeling and inference for forecasting and studying public opinion
  Basics of Linear Regression
  Data Visualization: How to create use data to create compelling graphics
  偏重统计，课程也涉及了应用（也是657= =）
• Columbia Machine Learning for Data Science and Analytics
  同样来自Columbia大学，和上面那门一看就很像，这门课目前评价不高
• 除此之外，edX上还有不少好课，比如Harvard的Justice，如果你需要拿个证书的话......

3. Udacity（待补充）

• 目前接触的比较少，似乎有data anlytics的纳米学位？

4. Youtube

• 油管上还有很多其他的好课，以及Open Course比如Yale Open Course和MIT Open Course
  列举几个：
• ISLR
• MIT introduction to psychology

5.以及MIT Open Course（Sorry, 只发现了这一个Open Course系统）

• 里面有相当多的课，有些需要下载专用软件
• MIT Statistical Thinking and Data Analysis
  This course follows the main outline of the course textbook very closely, skipping over various parts:
  Tamhane, Ajit C., and Dorothy D. Dunlop.
  Statistics and Data Analysis: From Elementary to Intermediate. Prentice Hall, 1999. ISBN: 9780137444267.
  This is an introductory statistics class, assuming probability as a prerequisite. We will review probability (Chapter 2), discuss sampling techniques (Chapter 3), data summarization (Chapter 4), common sampling distributions (Chapter 5), statistical inference and hypothesis testing (Chapters 6-9), regression (Chapters 10-11), and nonparametric inference (Chapter 14).