Columbia Data Science course, Fall 2012
I am blogging Rachel Schutt’s Columbia Data Science course in the Fall of 2012.
- Week 1: What is data science?
- Week 2: RealDirect, linear regression, k-nearest neighbors
- Week 3: Naive Bayes, Laplace Smoothing, scraping data off the web
- Week 4: K-means, Classifiers, Logistic Regression, Evaluation
- Week 5: GetGlue, time series, financial modeling, advanced regression, and ethics
- Week 6: Kaggle, crowd-sourcing, decision trees, random forests, social networks, and experimental design
- Week 7: Hunch.com, recommendation engines, SVD, alternating least squares, convexity, filter bubbles
- Week 8: Visualization, Broadening the definition of data science, Square, fraud detection
- Week 9: Morningside Analytics, network analysis, data journalism
- Week 10: Observational studies, confounders, and epidemiology
- Week 11: Estimating causal effects
- Week 12: Predictive modeling, data leakage, and model evaluation
- Week 13: MapReduce
- Week 14: Presentations
Leave a Reply
52 Shades of Greed card decks now available for purchase!
Go here and buy a bunch!
Do you happen to know if Columbia provides distance learning ?