- Simply Statistics: Written by the Biostatistics professors at Johns Hopkins University who also run Coursera's Data Science Specialization
- yhat's blog: Beginner-friendly content, usually in Python
- No Free Hunch (Kaggle's blog): Mostly interviews with competition winners, or updates on their competitions
- FastML: Various machine learning content, often with code
- Edwin Chen: Infrequently updated, but long and thoughtful pieces
- FiveThirtyEight: Tons of timely data-related content
- Machine Learning Mastery: Frequent posts on machine learning, very accessible
- Data School: Kevin Markham's blog! Beginner-focused, with reference guides and videos
- MLWave: Detailed posts on Kaggle competitions, by a Kaggle Master
- Data Science 101: Short, frequent content about all aspects of data science
- ML in the Valley: Thoughtful pieces by the Director of Analytics at Codecademy
- DataTau: Like Hacker News, but for data
- MachineLearning on reddit: Very active subreddit
- Quora's Machine Learning section: Lots of interesting Q&A
- KDnuggets: Data mining news, jobs, classes and more
- Data Community DC: Coordinates six local data-related meetup groups
- District Data Labs: Offers courses and other projects to local data scientists
- Coursera's Data Science Specialization: Nine courses (running every month) and a Capstone project, taught in R
- Stanford's Statistical Learning: By the authors of An Introduction to Statistical Learning and Elements of Statistical Learning, taught in R, highly recommended, running January through April 2015 (preview the lecture videos)
- Coursera's Machine Learning (Andrew Ng): Andrew Ng's acclaimed course, taught in MATLAB/Octave (preview the lecture videos)
- Coursera's Machine Learning (Pedro Domingos): No upcoming sessions (preview the lecture videos)
- Caltech's Learning from Data: Widely praised, not language-specific
- Udacity's Data Analyst Nanodegree: Project-based curriculum using Python, R, MapReduce, MongoDB
- Coursera's Data Mining Specialization: Brand new specialization beginning February 2015
- Coursera's Natural Language Processing: No upcoming sessions, but lectures and slides are available
- SlideRule's Data Analysis Learning Path: Curated content from various online classes
- Udacity's Intro to Artificial Intelligence: Taught by Peter Norvig and Sebastian Thrun
- Coursera's Neural Networks for Machine Learning: Taught by Geoffrey Hinton, no upcoming sessions
- statistics.com: Many online courses in data science
- CourseTalk: Read reviews of online courses
- Harvard's CS109 Data Science: Similar topics as General Assembly's course
- Columbia's Data Mining Class: Excellent slides
- Harvard's CS171 Visualization: Includes programming in D3
- Comparison of data science bootcamps: Up-to-date list maintained by a Zipfian Academy graduate
- Zipfian Academy: Offers Data Science Immersive, Data Engineering Immersive, Master's in Big Data (San Francisco, but possibly expanding)
- Data Science Retreat: Primarily uses R (Berlin)
- Metis Data Science Bootcamp: Newer bootcamp (New York)
- Persontyle: Various course offerings (based in London)
- Software Carpentry: Two-day workshops, primarily for researchers and hosted by universities (worldwide)
- Knowledge Discovery and Data Mining (KDD): Hosted by ACM (New York)
- O'Reilly Strata + Hadoop World: Big focus on "big data" (San Jose, London, New York)
- PyData: For developers and users of Python data tools (worldwide)
- PyCon: For developers and users of Python (Montreal in April 2015)
- An Introduction to Statistical Learning with Applications in R (free PDF)
- Elements of Statistical Learning (free PDF)
- Think Stats (free PDF or HTML)
- Mining of Massive Datasets (free PDF)
- Python for Informatics (free PDF or HTML)
- Statistics: Methods and Applications (free HTML)
- Python for Data Analysis
- Data Smart: Using Data Science to Transform Information into Insight
- Sams Teach Yourself SQL in 10 Minutes
- Open Source Data Science Masters: Huge list of resources
- Data Science Trello Board: Another list of resources
- The Hitchhiker's Guide to Python: Online guide to understanding Python and getting good at it
- Python Reference: Python tips, tutorials, and more
- videolectures.net: Tons of academic videos
- Metacademy: Quick summary of many machine learning terms, with links to resources for learning more