北美+德国18名校的数据挖掘、数据分析、人工智能及机器学习课程资源汇总

Quora

• What is Data Science?
• How do I become a Data Scientist?
• How does Data Science differ from traditional statistical analysis?

Related Courses

• Concepts in Computing with Data, Berkeley
• Practical Machine Learning, Berkeley
• Artificial Intelligence, Berkeley
• Visualization, Berkeley
• Data Mining and Analytics in Intelligent Business Services, Berkeley
• Data Science and Analytics: Thought Leaders, Berkeley
• Machine Learning, Stanford
• Paradigms for Computing with Data, Stanford
• Mining Massive Data Sets, Stanford
• Data Visualization, Stanford
• Algorithms for Massive Data Set Analysis, Stanford
• Research Topics in Interactive Data Analysis, Stanford
• Data Mining, Stanford
• Machine Learning, CMU
• Statistical Computing, CMU
• Machine Learning with Large Datasets, CMU
• Machine Learning, MIT
• Data Mining, MIT
• Statistical Learning Theory and Applications, MIT
• Data Literacy, MIT
• Introduction to Data Mining, UIUC
• Learning from Data, Caltech
• Introduction to Statistics, Harvard
• Data-Intensive Information Processing Applications, University of Maryland
• Dealing with Massive Data, Columbia
• Data-Driven Modeling, Columbia
• Introduction to Data Mining and Analysis, Georgia Tech
• Computational Data Analysis: Foundations of Machine Learning and Da…, Georgia Tech
• Applied Statistical Computing, Iowa State
• Data Visualization, Rice
• Data Warehousing and Data Mining, NYU
• Data Mining in Engineering, Toronto
• Machine Learning and Data Mining, UC Irvine
• Knowledge Discovery from Data, Cal Poly
• Large Scale Learning, University of Chicago
• Data Science: Large-scale Advanced Data Analysis, University of Florida
• Strategies for Statistical Data Analysis, Universität Leipzig

Related Workshops

• Data Bootcamp, Strata 2011
• Machine Learning Summer School, Purdue 2011
• Looking at Data

Books

• Competing on Analytics
• Analytics at Work
• Super Crunchers
• The Numerati
• Data Driven
• Data Source Handbook
• Programming Collective Intelligence
• Mining the Social Web
• Data Analysis with Open Source Tools
• Visualizing Data
• The Visual Display of Quantitative Information
• Envisioning Information
• Visual Explanations: Images and Quantities, Evidence and Narrative
• Beautiful Evidence
• Think Stats
• Data Analysis Using Regression and Multilevel/Hierarchical Models
• Applied Longitudinal Data Analysis
• Design of Observational Studies
• Statistical Rules of Thumb
• All of Statistics
• A Handbook of Statistical Analyses Using R
• Mathematical Statistics and Data Analysis
• The Elements of Statistical Learning
• Counterfactuals and Causal Inference
• Mining of Massive Data Sets
• Data Analysis: What Can Be Learned From the Past 50 Years
• Bias and Causation
• Regression Modeling Strategies
• Probably Not
• Statistics as Principled Argument
• The Practice of Data Analysis

Videos

• Lies, damned lies and statistics (about TEDTalks)
  
• The Joy of Stats
• Journalism in the Age of Data