Required Knowledge for a Data Scientist

Data Science 101, by Ryan Swanstrom, a great resource for budding data scientists like me, recently posted a must-read list of all the concepts a data scientist should know. Here’s the list he came up with:

  • linear algebra
  • basic statistics
  • linear and logistic regression
  • data mining
  • predictive modeling
  • cluster analysis
  • association rules
  • market basket analysis
  • decision trees
  • time-series analysis
  • forecasting
  • machine learning
  • Bayesian and Monte Carlo Statistics
  • matrix operations
  • sampling
  • text analytics
  • summarization
  • classification
  • primary components analysis
  • experimental design
  • unsupervised learning
  • constrained optimization

Although I’m familiar with some of these, from my introductory statistics and data mining courses through UCSD Extension, there’s still a lot to be learned – and mastered.

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