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At the request of many prospective participants, here's an update about our DSA (Data Science Apprenticeship). Also, I have added a few large data sets, new projects and more material. [size=1em]Click here for details.

If you have already earned a data science certificate or diploma, but was not requested to develop and use your own API in batch mode, and harvest/work on a data set with at least 50 million observations in a distributed environment, then it's time to learn the real stuff that will land you a real job!

Klein Bottle

[size=1em]Click here for a general overview of our apprenticeship. We have published the data and source code for our big data keyword correlation API. [size=1em]Read the material and download the three files (and post your comments if you have questions, I'll reply ASAP): it will teach you how API's work, and how to write your first API from scratch!

Our next API example will come with the source code of a web crawler, and will illustrate how to detect copyright infringement or how to detect the original, first version of an article published in multiple news outlets (doing a better job than Google).

All the training material will be offered for free to everyone. We have not yet put everything into a nice booklet, but some of the content is already available:

A few data sets available for download, from the following articles:

• [size=1em]Source code for our Big Data keyword correlation API
• [size=1em]Great statistical analysis: forecasting meteorite hits
• [size=1em]Fast clustering algorithms for massive datasets
• [size=1em]53.5 billion clicks dataset available for benchmarking and testing
• [size=1em]Over 5,000,000 financial, economic and social datasets
• [size=1em]New pattern to predict stock prices, multiplies return by factor 5
• [size=1em]3.5 billion web pages
• [size=1em]Another large data set - 250 million data points - available for do...
• 125 Years of Public Health Data Available for Download
• [size=1em]Two big datasets to challenge your data science expertise *
• [size=1em]From the trenches: real data science project (Google Analytics) *
• [size=1em]Data sets and other machine learning resources from UC Irvine *
  

The following articles will be included in our curriculum, so you can start reading them now

• [size=1em]Fast clustering algorithms for massive datasets
• [size=1em]Fast Combinatorial Feature Selection with New Definition of Predict...
• [size=1em]Jackknife logistic and linear regression for clustering and predict... *
• [size=1em]Discussion about outliers and criticizing charts *
• Learn experimental design with our live, real-time ongoing analysis *
• The best kept secret about linear and logistic regression *
• [size=1em]Attribution Modeling
• [size=1em]Internet Topology Mapping
• Correlation and R-Squared for Big Data
• [size=1em]From chaos to clusters - statistical modeling without models
• [size=1em]Example of architecture for AaaS (Analytics as a Service)
• [size=1em]Other source code posted on Analyticbridge
• [size=1em]Simple solutions to make videos with R
• [size=1em]What Map Reduce can't do
• [size=1em]The curse of big data
• [size=1em]Correlation vs. causation
• [size=1em]Three classes of metrics: centrality, volatility, and bumpiness
• Data Science dictionary
• Data Science tools
• A new random number generator
• 66 job interview questions for data scientists
• [size=1em]Data Science eBook (2nd Edition)
• [size=1em]The art of steganography
• [size=1em]Eight worst predictive modeling techniques
• [size=1em]Hidden decision trees: a modern scoring methodology
• [size=1em]Why and how to build a data dictionary for big data sets
• [size=1em]How to build simple, accurate, data-driven, model-free confidence i...
• [size=1em]A Couple Good Python Resources for Data Science
• When a data glitch turns great data into worthless gibberish
• How to detect a pattern? Problem and solution
• R in your Browser
• A new, fast Excel for big data
• Marrying computer science, statistics and domain expertize
• Building better search tools: problems and solutions
• [size=1em]The Data Science Formula and [size=1em]Clustering data scientists (student project)
• [size=1em]Detecting Patterns with the Naked Eye
  

List of potential projects for students:

• [size=1em][size=1em]Click here for some suggestions
  

Starred items (*) are recent additions.