[Coursera Specialization] Data Science by Roger D. Peng, Jeff Leek, Brian Caffo
File List
- 7. Regression Models/07 - Newly Recorded Video Lectures/07 - 02_02 Multivariate examples/8 - 7 - 02_02 Multivariate examples.mp4 98.0 MB
- 7. Regression Models/05 - Whole lectures/08 - 02_02/5 - 8 - 02_02.mp4 88.8 MB
- 4. Exploratory Data Analysis/05 - Week 4/02 - Air Pollution Case Study [4035]/5 - 2 - Air Pollution Case Study [4035].mp4 72.0 MB
- 7. Regression Models/07 - Newly Recorded Video Lectures/06 - 02_01 Multivariate statistical models/8 - 6 - 02_01 Multivariate statistical models.mp4 53.5 MB
- 5. Reproducible Research/04 - Week 4/03 - Case Study High Throughput Biology [3051]/4 - 3 - Case Study High Throughput Biology [3051].mp4 50.6 MB
- 6. Statistical Inference/06 - Homework Videos/04 - Homework 4/10 - 4 - Homework 4.mp4 48.5 MB
- 7. Regression Models/05 - Whole lectures/07 - 02_01/5 - 7 - 02_01.mp4 44.4 MB
- 7. Regression Models/05 - Whole lectures/14 - 03_03/5 - 14 - 03_03.mp4 43.5 MB
- 7. Regression Models/05 - Whole lectures/13 - 03_02/5 - 13 - 03_02.mp4 41.9 MB
- 7. Regression Models/07 - Newly Recorded Video Lectures/01 - 01_01 Introduction and Least Squares/8 - 1 - 01_01 Introduction and Least Squares.mp4 41.3 MB
- 9. Developing Data Products/03 - Week 4/06 - yhat (Part 1) (24-39)/4 - 6 - yhat (Part 1) (2439).mp4 40.1 MB
- 7. Regression Models/07 - Newly Recorded Video Lectures/03 - 01_03 Least Squares/8 - 3 - 01_03 Least Squares.mp4 38.7 MB
- 7. Regression Models/05 - Whole lectures/16 - 01_07/5 - 16 - 01_07.mp4 37.0 MB
- 9. Developing Data Products/04 - Whole lectures/01 - Shiny/5 - 1 - Shiny.mp4 36.9 MB
- 7. Regression Models/03 - Week 3/02 - 02_02_b Dummy variables (27-08)/3 - 2 - 02_02_b Dummy variables (2708).mp4 35.2 MB
- 7. Regression Models/03 - Week 3/03 - 02_02_c Interactions (26-29)/3 - 3 - 02_02_c Interactions (2629).mp4 34.4 MB
- 7. Regression Models/05 - Whole lectures/11 - 02_05/5 - 11 - 02_05.mp4 33.5 MB
- 9. Developing Data Products/03 - Week 4/03 - Building R Packages Demo (18-00)/4 - 3 - Building R Packages Demo (1800).mp4 32.0 MB
- 9. Developing Data Products/04 - Whole lectures/04 - R Studio Presenter/5 - 4 - R Studio Presenter.mp4 31.9 MB
- 6. Statistical Inference/02 - Second Week/10 - 07 03 Asymptotics and confidence intervals (20-10)/2 - 10 - 07 03 Asymptotics and confidence intervals (2010).mp4 31.1 MB
- 9. Developing Data Products/04 - Whole lectures/02 - shiny2/5 - 2 - shiny2.mp4 31.1 MB
- 6. Statistical Inference/04 - Fourth Week/05 - 12 Multiple Comparisons (25-22)/4 - 5 - 12 Multiple Comparisons (2522).mp4 30.5 MB
- 7. Regression Models/05 - Whole lectures/01 - 01_01/5 - 1 - 01_01.mp4 29.9 MB
- 6. Statistical Inference/06 - Homework Videos/02 - Homework 2/10 - 2 - Homework 2.mp4 29.5 MB
- 7. Regression Models/07 - Newly Recorded Video Lectures/05 - 01_05 Statistical linear regression models/8 - 5 - 01_05 Statistical linear regression models.mp4 28.8 MB
- 9. Developing Data Products/04 - Whole lectures/03 - Slidify/5 - 3 - Slidify.mp4 28.7 MB
- 7. Regression Models/05 - Whole lectures/06 - 01_06/5 - 6 - 01_06.mp4 28.6 MB
- 6. Statistical Inference/06 - Homework Videos/01 - Homework 1/10 - 1 - Homework 1.mp4 27.6 MB
- 4. Exploratory Data Analysis/05 - Week 4/01 - Clustering Case Study [1451]/clusteringEx_data.zip 27.3 MB
- 7. Regression Models/05 - Whole lectures/03 - 01_03/5 - 3 - 01_03.mp4 26.9 MB
- 7. Regression Models/05 - Whole lectures/05 - 01_05/5 - 5 - 01_05.mp4 23.4 MB
- 6. Statistical Inference/02 - Second Week/06 - 06 02 Normal distribution (15-12)/2 - 6 - 06 02 Normal distribution (1512).mp4 23.4 MB
- 8. Practical Machine Learning/02 - Week 2/06 - Covariate creation (17-31)/2 - 6 - Covariate creation (1731).mp4 22.8 MB
- 7. Regression Models/05 - Whole lectures/15 - 03_04/5 - 15 - 03_04.mp4 22.7 MB
- 6. Statistical Inference/03 - Third Week/08 - 09 04 Two group testing (17-54)/3 - 8 - 09 04 Two group testing (1754).mp4 22.4 MB
- 7. Regression Models/05 - Whole lectures/10 - 02_04/5 - 10 - 02_04.mp4 22.0 MB
- 9. Developing Data Products/04 - Whole lectures/06 - rCharts/5 - 6 - rCharts.mp4 21.8 MB
- 6. Statistical Inference/06 - Homework Videos/03 - Homework 3/10 - 3 - Homework 3.mp4 21.8 MB
- 7. Regression Models/05 - Whole lectures/09 - 02_03/5 - 9 - 02_03.mp4 21.7 MB
- 9. Developing Data Products/03 - Week 4/07 - yhat (Part 2) (11-38)/4 - 7 - yhat (Part 2) (1138).mp4 21.2 MB
- 6. Statistical Inference/03 - Third Week/03 - 08 03 Independent group T intervals (14-36)/3 - 3 - 08 03 Independent group T intervals (1436).mp4 21.1 MB
- 5. Reproducible Research/01 - Week 1/07 - Structure of a Data Analysis (part 2) [1741]/1 - 8 - Structure of a Data Analysis (part 2) [1741].mp4 21.0 MB
- 5. Reproducible Research/04 - Week 4/02 - Case Study Air Pollution [1412]/4 - 2 - Case Study Air Pollution [1412].mp4 20.9 MB
- 7. Regression Models/05 - Whole lectures/12 - 03_01/5 - 12 - 03_01.mp4 20.2 MB
- 7. Regression Models/07 - Newly Recorded Video Lectures/04 - 01_04 Regression to the Mean/8 - 4 - 01_04 Regression to the Mean.mp4 19.9 MB
- 7. Regression Models/03 - Week 3/01 - 02_02_a Multivariable regression examples (14-38)/3 - 1 - 02_02_a Multivariable regression examples (1438).mp4 19.5 MB
- 7. Regression Models/02 - Week 2/09 - 01_07_c Prediction Intervals (14-13)/2 - 9 - 01_07_c Prediction Intervals (1413).mp4 19.0 MB
- 7. Regression Models/05 - Whole lectures/04 - 01_04/5 - 4 - 01_04.mp4 18.9 MB
- 5. Reproducible Research/02 - Week 2/01 - Coding Standards in R [859]/2 - 1 - Coding Standards in R [859].mp4 18.9 MB
- 4. Exploratory Data Analysis/03 - Week 2/04 - ggplot2 (part 2) [1353]/3 - 4 - ggplot2 (part 2) [1353].mp4 18.4 MB
- 9. Developing Data Products/03 - Week 4/04 - R Classes and Methods (Part 1) (13-50)/4 - 4 - R Classes and Methods (Part 1) (1350).mp4 18.1 MB
- 6. Statistical Inference/01 - First Week/05 - 02 03 Probability density functions (13-27)/1 - 5 - 02 03 Probability density functions (1327).mp4 17.9 MB
- 6. Statistical Inference/04 - Fourth Week/02 - 11 02 Calculating Power (12-51)/4 - 2 - 11 02 Calculating Power (1251).mp4 17.8 MB
- 7. Regression Models/04 - Week 4/08 - 03_03_b Poisson Regression Example (14-12)/4 - 8 - 03_03_b Poisson Regression Example (1412).mp4 17.8 MB
- 9. Developing Data Products/02 - Week 2/08 - RStudio Presenter 2 Authoring details (11-14)/3 - 8 - RStudio Presenter 2 Authoring details (1114).mp4 17.6 MB
- 7. Regression Models/04 - Week 4/05 - 03_02_b GLMs and Odds (14-03)/4 - 5 - 03_02_b GLMs and Odds (1403).mp4 17.6 MB
- 3. Getting and Cleaning Data/03 - Week 3/06 - Managing Data Frames with dplyr - Basic Tools/3 - 6 - Managing Data Frames with dplyr - Basic Tools.mp4 17.5 MB
- 8. Practical Machine Learning/02 - Week 2/07 - Preprocessing with principal components analysis (14-07)/2 - 7 - Preprocessing with principal components analysis (1407).mp4 17.4 MB
- 9. Developing Data Products/03 - Week 4/02 - R Packages (Part 2) (14-59)/4 - 2 - R Packages (Part 2) (1459).mp4 17.1 MB
- 8. Practical Machine Learning/04 - Week 4/01 - Regularized regression (13-20)/4 - 1 - Regularized regression (1320).mp4 16.8 MB
- 4. Exploratory Data Analysis/05 - Week 4/01 - Clustering Case Study [1451]/5 - 1 - Clustering Case Study [1451].mp4 16.8 MB
- 5. Reproducible Research/04 - Week 4/01 - Caching Computations [1116]/4 - 1 - Caching Computations [1116].mp4 16.5 MB
- 2. R Programming/03 - Week 2/06 - Your First R Function [1029]/3 - 6 - Your First R Function [1029].mp4 16.5 MB
- 7. Regression Models/02 - Week 2/08 - 01_07_b T Tests for Regression Coefficients (12-33)/2 - 8 - 01_07_b T Tests for Regression Coefficients (1233).mp4 16.3 MB
- 7. Regression Models/02 - Week 2/11 - 02_01_b Multivariable Least Squares (12-59)/2 - 11 - 02_01_b Multivariable Least Squares (1259).mp4 16.2 MB
- 8. Practical Machine Learning/03 - Week 3/01 - Predicting with trees (12-51)/3 - 1 - Predicting with trees (1251).mp4 16.2 MB
- 4. Exploratory Data Analysis/02 - Week 1/08 - Base Plotting Demonstration [1656]/2 - 8 - Base Plotting Demonstration [1656].mp4 16.0 MB
- 8. Practical Machine Learning/02 - Week 2/08 - Predicting with Regression (12-22)/2 - 8 - Predicting with Regression (1222).mp4 15.8 MB
- 7. Regression Models/04 - Week 4/09 - 03_03_c Poisson Rate Models (12-53)/4 - 9 - 03_03_c Poisson Rate Models (1253).mp4 15.8 MB
- 5. Reproducible Research/03 - Week 3/04 - Reproducible Research Checklist (part 2) [1020]/3 - 4 - Reproducible Research Checklist (part 2) [1020].mp4 15.4 MB
- 7. Regression Models/04 - Week 4/06 - 03_02_c More on Odds (12-29)/4 - 6 - 03_02_c More on Odds (1229).mp4 15.3 MB
- 5. Reproducible Research/01 - Week 1/06 - Structure of a Data Analysis (part 1) [1229]/1 - 7 - Structure of a Data Analysis (part 1) [1229].mp4 14.9 MB
- 2. R Programming/03 - Week 2/12 - Coding Standards [859]/3 - 12 - Coding Standards [859].mp4 14.8 MB
- 8. Practical Machine Learning/03 - Week 3/05 - Model Based Prediction (11-39)/3 - 5 - Model Based Prediction (1139).mp4 14.5 MB
- 8. Practical Machine Learning/02 - Week 2/09 - Predicting with Regression Multiple Covariates (11-12)/2 - 9 - Predicting with Regression Multiple Covariates (1112).mp4 14.5 MB
- 7. Regression Models/01 - Week 1/09 - 01_03_c Linear Least Squares Solved (11-33)/1 - 9 - 01_03_c Linear Least Squares Solved (1133).mp4 14.4 MB
- 8. Practical Machine Learning/02 - Week 2/04 - Plotting predictors (10-39)/2 - 4 - Plotting predictors (1039).mp4 14.2 MB
- 7. Regression Models/02 - Week 2/06 - 01_06_c Residual Variation (11-20)/2 - 6 - 01_06_c Residual Variation (1120).mp4 14.1 MB
- 5. Reproducible Research/01 - Week 1/08 - Organizing Your Analysis [1105]/1 - 9 - Organizing Your Analysis [1105].mp4 14.1 MB
- 6. Statistical Inference/01 - First Week/01 - 01 01 Introduction (7-05)/1 - 1 - 01 01 Introduction (705).mp4 14.0 MB
- 7. Regression Models/01 - Week 1/11 - 01_04_b Regression to the Mean Example (10-46)/1 - 11 - 01_04_b Regression to the Mean Example (1046).mp4 13.9 MB
- 8. Practical Machine Learning/01 - Week 1/06 - Types of errors (10-35)/1 - 6 - Types of errors (1035).mp4 13.9 MB
- 8. Practical Machine Learning/02 - Week 2/05 - Basic preprocessing (10-52)/2 - 5 - Basic preprocessing (1052).mp4 13.6 MB
- 6. Statistical Inference/04 - Fourth Week/08 - 13 03 Notes on the bootstrap (10-20)/4 - 8 - 13 03 Notes on the bootstrap (1020).mp4 13.4 MB
- 9. Developing Data Products/01 - Week 1/19 - plotly/2 - 19 - plotly.mp4 13.4 MB
- 9. Developing Data Products/04 - Whole lectures/07 - plotly/5 - 7 - plotly.mp4 13.4 MB
- 7. Regression Models/03 - Week 3/12 - 02_05_b Variance inflation (10-33)/3 - 12 - 02_05_b Variance inflation (1033).mp4 13.3 MB
- 1. The Data Scientist's Toolbox/Week 03/3 - 4 - Experimental Design (15_59).mp4 13.3 MB
- 9. Developing Data Products/03 - Week 4/05 - R Classes and Methods (Part 2) (11-19)/4 - 5 - R Classes and Methods (Part 2) (1119).mp4 13.3 MB
- 7. Regression Models/07 - Newly Recorded Video Lectures/02 - 01_02 Basic notation/8 - 2 - 01_02 Basic notation.mp4 13.3 MB
- 6. Statistical Inference/03 - Third Week/09 - 10 01 Pvalues (7-50)/3 - 9 - 10 01 Pvalues (750).mp4 12.9 MB
- 6. Statistical Inference/01 - First Week/07 - 03 02 Bayes rule (7-52)/1 - 7 - 03 02 Bayes rule (752).mp4 12.8 MB
- 7. Regression Models/04 - Week 4/10 - 03_04_a Fitting Functions (9-52)/4 - 10 - 03_04_a Fitting Functions (952).mp4 12.8 MB
- 7. Regression Models/02 - Week 2/13 - 02_01_d Multivariable Linear Models Interpretation (9-46)/2 - 13 - 02_01_d Multivariable Linear Models Interpretation (946).mp4 12.7 MB
- 6. Statistical Inference/02 - Second Week/09 - 07 02 Asymptotics and the CLT (8-27)/2 - 9 - 07 02 Asymptotics and the CLT (827).mp4 12.6 MB
- 9. Developing Data Products/01 - Week 1/08 - More advanced shiny discussion, reactivity (9-30)/2 - 8 - More advanced shiny discussion, reactivity (930).mp4 12.6 MB
- 5. Reproducible Research/02 - Week 2/08 - knitr (part 4) [921]/2 - 8 - knitr (part 4) [921].mp4 12.5 MB
- 9. Developing Data Products/01 - Week 1/17 - GoogleVis (9-34)/2 - 17 - GoogleVis (934).mp4 12.4 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 2 - Command Line Interface (16_04).mp4 12.4 MB
- 8. Practical Machine Learning/01 - Week 1/03 - Relative importance of steps (9-45)/1 - 3 - Relative importance of steps (945).mp4 12.3 MB
- 3. Getting and Cleaning Data/02 - Week 2/01 - Reading from MySQL (14-44)/2 - 1 - Reading from MySQL (1444).mp4 12.2 MB
- 6. Statistical Inference/02 - Second Week/03 - 05 03 Standard error of the mean (7-12)/2 - 3 - 05 03 Standard error of the mean (712).mp4 12.1 MB
- 7. Regression Models/02 - Week 2/12 - 02_01_c More Multivariable Least Squares (8-35)/2 - 12 - 02_01_c More Multivariable Least Squares (835).mp4 11.9 MB
- 2. R Programming/03 - Week 2/13 - Dates and Times [1029]/3 - 13 - Dates and Times [1029].mp4 11.8 MB
- 6. Statistical Inference/03 - Third Week/01 - 08 01 T confidence intervals (9-12)/3 - 1 - 08 01 T confidence intervals (912).mp4 11.8 MB
- 6. Statistical Inference/04 - Fourth Week/04 - 11 04 T test power (8-02)/4 - 4 - 11 04 T test power (802).mp4 11.6 MB
- 2. R Programming/02 - Week 1/02 - Overview and History of R [1607]/2 - 2 - Overview and History of R [1607].mp4 11.6 MB
- 3. Getting and Cleaning Data/01 - Week 1/07 - Reading XML (12-39)/1 - 7 - Reading XML (1239).mp4 11.5 MB
- 8. Practical Machine Learning/03 - Week 3/02 - Bagging (9-13)/3 - 2 - Bagging (913).mp4 11.4 MB
- 7. Regression Models/05 - Whole lectures/02 - 01_02/5 - 2 - 01_02.mp4 11.3 MB
- 2. R Programming/05 - Week 4/06 - R Profiler (part 2) [1026]/5 - 6 - R Profiler (part 2) [1026].mp4 11.2 MB
- 2. R Programming/01 - Background Material/05 - Writing Code Setting Your Working Directory (Mac)/1 - 5 - Writing Code Setting Your Working Directory (Mac).mp4 11.2 MB
- 7. Regression Models/03 - Week 3/13 - 02_05_c Model comparison and search (8-05)/3 - 13 - 02_05_c Model comparison and search (805).mp4 11.1 MB
- 8. Practical Machine Learning/01 - Week 1/05 - Prediction study design (9-05)/1 - 5 - Prediction study design (905).mp4 11.1 MB
- 5. Reproducible Research/03 - Week 3/03 - Reproducible Research Checklist (part 1) [822]/3 - 3 - Reproducible Research Checklist (part 1) [822].mp4 11.1 MB
- 6. Statistical Inference/04 - Fourth Week/09 - 13 04 Permutation tests (9-07)/4 - 9 - 13 04 Permutation tests (907).mp4 11.0 MB
- 7. Regression Models/02 - Week 2/05 - 01_06_b Properties of Residuals (8-48)/2 - 5 - 01_06_b Properties of Residuals (848).mp4 11.0 MB
- 8. Practical Machine Learning/01 - Week 1/02 - What is prediction (8-39)/1 - 2 - What is prediction (839).mp4 11.0 MB
- 9. Developing Data Products/01 - Week 1/03 - Shiny 1 Introduction to Shiny (8-36)/2 - 3 - Shiny 1 Introduction to Shiny (836).mp4 10.9 MB
- 6. Statistical Inference/01 - First Week/11 - 04 03 Expected values for PDFs (7-46)/1 - 11 - 04 03 Expected values for PDFs (746).mp4 10.9 MB
- 4. Exploratory Data Analysis/02 - Week 1/02 - Principles of Analytic Graphics [1211]/2 - 2 - Principles of Analytic Graphics [1211].mp4 10.8 MB
- 8. Practical Machine Learning/04 - Week 4/03 - Forecasting/4 - 3 - Forecasting.mp4 10.6 MB
- 8. Practical Machine Learning/01 - Week 1/01 - Prediction motivation (8-26)/1 - 1 - Prediction motivation (826).mp4 10.5 MB
- 6. Statistical Inference/01 - First Week/04 - 02 02 Probability mass functions (7-14)/1 - 4 - 02 02 Probability mass functions (714).mp4 10.5 MB
- 5. Reproducible Research/01 - Week 1/05 - Scripting Your Analysis [436]/1 - 6 - Scripting Your Analysis [436].mp4 10.2 MB
- 8. Practical Machine Learning/01 - Week 1/08 - Cross validation (8-20)/1 - 8 - Cross validation (820).mp4 10.1 MB
- 5. Reproducible Research/01 - Week 1/02 - Reproducible Research Concepts and Ideas (part 1) [711]/1 - 3 - Reproducible Research Concepts and Ideas (part 1) [711].mp4 10.1 MB
- 9. Developing Data Products/02 - Week 2/10 - Very quick introduction to gh-pages/3 - 10 - Very quick introduction to gh-pages.mp4 10.1 MB
- 5. Reproducible Research/02 - Week 2/04 - R Markdown Demonstration [724]/2 - 4 - R Markdown Demonstration [724].mp4 10.0 MB
- 7. Regression Models/04 - Week 4/11 - 03_04_b Fun Example (8-02)/4 - 11 - 03_04_b Fun Example (802).mp4 10.0 MB
- 7. Regression Models/04 - Week 4/07 - 03_03_a Poisson Regression (8-15)/4 - 7 - 03_03_a Poisson Regression (815).mp4 9.9 MB
- 4. Exploratory Data Analysis/03 - Week 2/06 - ggplot2 (part 4) [1038]/3 - 6 - ggplot2 (part 4) [1038].mp4 9.8 MB
- 7. Regression Models/01 - Week 1/04 - 01_01_d Regression through the origin (7-37)/1 - 4 - 01_01_d Regression through the origin (737).mp4 9.7 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 1 - Series Motivation (12_03).mp4 9.6 MB
- 3. Getting and Cleaning Data/03 - Week 3/02 - Summarizing Data (11-37)/3 - 2 - Summarizing Data (1137).mp4 9.6 MB
- 6. Statistical Inference/04 - Fourth Week/06 - 13 01 Bootstrapping (7-10)/4 - 6 - 13 01 Bootstrapping (710).mp4 9.5 MB
- 5. Reproducible Research/02 - Week 2/05 - knitr (part 1) [705]/2 - 5 - knitr (part 1) [705].mp4 9.5 MB
- 5. Reproducible Research/03 - Week 3/10 - Evidence-based Data Analysis (part 5) [756]/3 - 10 - Evidence-based Data Analysis (part 5) [756].mp4 9.3 MB
- 8. Practical Machine Learning/04 - Week 4/02 - Combining predictors (7-11)/4 - 2 - Combining predictors (711).mp4 9.3 MB
- 9. Developing Data Products/02 - Week 2/05 - Slidify more details (7-24)/3 - 5 - Slidify more details (724).mp4 9.3 MB
- 6. Statistical Inference/03 - Third Week/10 - 10 02 Pvalue further examples (5-54)/3 - 10 - 10 02 Pvalue further examples (554).mp4 9.2 MB
- 4. Exploratory Data Analysis/02 - Week 1/06 - Base Plotting System (part 1) [1120]/2 - 6 - Base Plotting System (part 1) [1120].mp4 9.2 MB
- 2. R Programming/05 - Week 4/05 - R Profiler (part 1) [1039]/5 - 5 - R Profiler (part 1) [1039].mp4 9.2 MB
- 2. R Programming/02 - Week 1/03 - Getting Help [1353]/2 - 3 - Getting Help [1353].mp4 9.2 MB
- 6. Statistical Inference/01 - First Week/03 - 02 01 Introduction to probability (6-13)/1 - 3 - 02 01 Introduction to probability (613).mp4 9.1 MB
- 7. Regression Models/03 - Week 3/11 - 02_05_a Some thoughts on model selection (6-38)/3 - 11 - 02_05_a Some thoughts on model selection (638).mp4 9.1 MB
- 9. Developing Data Products/03 - Week 4/01 - R Packages (Part 1) (7-11)/4 - 1 - R Packages (Part 1) (711).mp4 9.1 MB
- 8. Practical Machine Learning/03 - Week 3/04 - Boosting (7-08)/3 - 4 - Boosting (708).mp4 9.1 MB
- 6. Statistical Inference/02 - Second Week/07 - 06 03 Poisson (6-08)/2 - 7 - 06 03 Poisson (608).mp4 9.0 MB
- 7. Regression Models/04 - Week 4/03 - 03_01_c Variances and Quasi Likelihood (7-05)/4 - 3 - 03_01_c Variances and Quasi Likelihood (705).mp4 9.0 MB
- 8. Practical Machine Learning/02 - Week 2/03 - Training options (7-15)/2 - 3 - Training options (715).mp4 9.0 MB
- 3. Getting and Cleaning Data/04 - Week 4/01 - Editing Text Variables (10-46)/4 - 1 - Editing Text Variables (1046).mp4 9.0 MB
- 7. Regression Models/04 - Week 4/04 - 03_02_a Binary Data GLMs (7-11)/4 - 4 - 03_02_a Binary Data GLMs (711).mp4 8.9 MB
- 5. Reproducible Research/03 - Week 3/05 - Reproducible Research Checklist (part 3) [654]/3 - 5 - Reproducible Research Checklist (part 3) [654].mp4 8.9 MB
- 3. Getting and Cleaning Data/01 - Week 1/09 - The data.table Package (11-18)/1 - 9 - The data.table Package (1118).mp4 8.9 MB
- 2. R Programming/01 - Background Material/04 - Writing Code Setting Your Working Directory (Windows)/1 - 4 - Writing Code Setting Your Working Directory (Windows).mp4 8.9 MB
- 8. Practical Machine Learning/03 - Week 3/03 - Random Forests (6-49)/3 - 3 - Random Forests (649).mp4 8.7 MB
- 6. Statistical Inference/03 - Third Week/07 - 09 03 T tests (7-04)/3 - 7 - 09 03 T tests (704).mp4 8.7 MB
- 4. Exploratory Data Analysis/03 - Week 2/05 - ggplot2 (part 3) [947]/3 - 5 - ggplot2 (part 3) [947].mp4 8.7 MB
- 8. Practical Machine Learning/01 - Week 1/04 - In and out of sample errors (6-57)/1 - 4 - In and out of sample errors (657).mp4 8.7 MB
- 9. Developing Data Products/02 - Week 2/07 - RStudio Presenter 1 Introduction and getting started (4-59)/3 - 7 - RStudio Presenter 1 Introduction and getting started (459).mp4 8.6 MB
- 7. Regression Models/03 - Week 3/10 - 02_04_c Residuals and diagnostics examples (6-32)/3 - 10 - 02_04_c Residuals and diagnostics examples (632).mp4 8.5 MB
- 3. Getting and Cleaning Data/03 - Week 3/03 - Creating New Variables (10-32)/3 - 3 - Creating New Variables (1032).mp4 8.5 MB
- 9. Developing Data Products/01 - Week 1/16 - rCharts mapping and discussion (5-32)/2 - 16 - rCharts mapping and discussion (532).mp4 8.4 MB
- 5. Reproducible Research/02 - Week 2/09 - Introduction to Peer Assessment 1/2 - 9 - Introduction to Peer Assessment 1.mp4 8.4 MB
- 7. Regression Models/02 - Week 2/02 - 01_05_b Interpreting Regression Coefficients (6-28)/2 - 2 - 01_05_b Interpreting Regression Coefficients (628).mp4 8.4 MB
- 2. R Programming/04 - Week 3/06 - Debugging Tools - Diagnosing the Problem [1233]/4 - 6 - Debugging Tools - Diagnosing the Problem [1233].mp4 8.4 MB
- 2. R Programming/02 - Week 1/14 - Reading Large Tables [708]/2 - 14 - Reading Large Tables [708].mp4 8.3 MB
- 4. Exploratory Data Analysis/02 - Week 1/05 - Plotting Systems in R [934]/2 - 5 - Plotting Systems in R [934].mp4 8.3 MB
- 8. Practical Machine Learning/02 - Week 2/01 - Caret package (6-16)/2 - 1 - Caret package (616).mp4 8.2 MB
- 5. Reproducible Research/03 - Week 3/01 - Communicating Results [654]/3 - 1 - Communicating Results [654].mp4 8.2 MB
- 6. Statistical Inference/01 - First Week/09 - 04 01 Expected values (5-14)/1 - 9 - 04 01 Expected values (514).mp4 8.0 MB
- 6. Statistical Inference/04 - Fourth Week/01 - 11 01 Power (4-54)/4 - 1 - 11 01 Power (454).mp4 8.0 MB
- 7. Regression Models/04 - Week 4/02 - 03_01_b GLM Examples (6-21)/4 - 2 - 03_01_b GLM Examples (621).mp4 7.9 MB
- 5. Reproducible Research/02 - Week 2/03 - R Markdown [635]/2 - 3 - R Markdown [635].mp4 7.9 MB
- 8. Practical Machine Learning/01 - Week 1/09 - What data should you use (6-01)/1 - 9 - What data should you use (601).mp4 7.8 MB
- 1. The Data Scientist's Toolbox/Week 03/3 - 1 - Types of Questions (9_09).mp4 7.7 MB
- 6. Statistical Inference/03 - Third Week/06 - 09 02 Example of choosing a rejection region (5-12)/3 - 6 - 09 02 Example of choosing a rejection region (512).mp4 7.6 MB
- 2. R Programming/03 - Week 2/09 - Scoping Rules - Symbol Binding [1032]/3 - 9 - Scoping Rules - Symbol Binding [1032].mp4 7.6 MB
- 7. Regression Models/02 - Week 2/03 - 01_05_c Statistical Regression Models Examples (6-00)/2 - 3 - 01_05_c Statistical Regression Models Examples (600).mp4 7.6 MB
- 9. Developing Data Products/01 - Week 1/15 - rCharts more examples (5-40)/2 - 15 - rCharts more examples (540).mp4 7.6 MB
- 3. Getting and Cleaning Data/01 - Week 1/03 - Components of Tidy Data (9-25)/1 - 3 - Components of Tidy Data (925).mp4 7.6 MB
- 7. Regression Models/03 - Week 3/09 - 02_04_b More on diagnostics (5-18)/3 - 9 - 02_04_b More on diagnostics (518).mp4 7.6 MB
- 5. Reproducible Research/01 - Week 1/03 - Reproducible Research Concepts and Ideas (part 2) [527]/1 - 4 - Reproducible Research Concepts and Ideas (part 2) [527].mp4 7.5 MB
- 7. Regression Models/03 - Week 3/04 - 02_03_a Multivariable simulation exercises (5-42)/3 - 4 - 02_03_a Multivariable simulation exercises (542).mp4 7.5 MB
- 7. Regression Models/01 - Week 1/03 - 01_01_c Least squares continued (5-38)/1 - 3 - 01_01_c Least squares continued (538).mp4 7.5 MB
- 7. Regression Models/02 - Week 2/01 - 01_05_a Statistical Linear Regression Models (5-58)/2 - 1 - 01_05_a Statistical Linear Regression Models (558).mp4 7.4 MB
- 9. Developing Data Products/02 - Week 2/01 - Presenting Data Analysis Writing a Data Report (3-18)/3 - 1 - Presenting Data Analysis Writing a Data Report (318).mp4 7.4 MB
- 7. Regression Models/01 - Week 1/07 - 01_03_a Linear Least Squares (6-01)/1 - 7 - 01_03_a Linear Least Squares (601).mp4 7.3 MB
- 4. Exploratory Data Analysis/03 - Week 2/07 - ggplot2 (part 5) [811]/3 - 7 - ggplot2 (part 5) [811].mp4 7.3 MB
- 6. Statistical Inference/02 - Second Week/01 - 05 01 Introduction to variability (4-57)/2 - 1 - 05 01 Introduction to variability (457).mp4 7.3 MB
- 5. Reproducible Research/02 - Week 2/02 - Markdown [515]/2 - 2 - Markdown [515].mp4 7.2 MB
- 4. Exploratory Data Analysis/01 - Background Material/05 - Setting Your Working Directory (Mac)/1 - 5 - Setting Your Working Directory (Mac).mp4 7.2 MB
- 3. Getting and Cleaning Data/03 - Week 3/04 - Reshaping Data (9-13)/3 - 4 - Reshaping Data (913).mp4 7.2 MB
- 9. Developing Data Products/02 - Week 2/02 - Slidify intro (5-32)/3 - 2 - Slidify intro (532).mp4 7.2 MB
- 2. R Programming/02 - Week 1/06 - Data Types - Vectors and Lists [627]/2 - 6 - Data Types - Vectors and Lists [627].mp4 7.2 MB
- 7. Regression Models/01 - Week 1/02 - 01_01_b Basic least squares (5-41)/1 - 2 - 01_01_b Basic least squares (541).mp4 7.2 MB
- 4. Exploratory Data Analysis/04 - Week 3/07 - Dimension Reduction (part 2) [926]/4 - 7 - Dimension Reduction (part 2) [926].mp4 7.1 MB
- 6. Statistical Inference/04 - Fourth Week/03 - 11 03 Notes on power (4-57)/4 - 3 - 11 03 Notes on power (457).mp4 7.0 MB
- 8. Practical Machine Learning/02 - Week 2/02 - Data slicing (5-40)/2 - 2 - Data slicing (540).mp4 7.0 MB
- 6. Statistical Inference/02 - Second Week/08 - 07 01 Asymptotics and LLN (4-28)/2 - 8 - 07 01 Asymptotics and LLN (428).mp4 6.9 MB
- 4. Exploratory Data Analysis/02 - Week 1/03 - Exploratory Graphs (part 1) [928]/2 - 3 - Exploratory Graphs (part 1) [928].mp4 6.9 MB
- 2. R Programming/02 - Week 1/13 - Reading Tabular Data [551]/2 - 13 - Reading Tabular Data [551].mp4 6.9 MB
- 9. Developing Data Products/01 - Week 1/09 - More advanced shiny, the reactive function (5-50)/2 - 9 - More advanced shiny, the reactive function (550).mp4 6.8 MB
- 5. Reproducible Research/04 - Week 4/04 - Commentaries on Data Analysis/4 - 4 - Commentaries on Data Analysis.mp4 6.8 MB
- 7. Regression Models/01 - Week 1/06 - 01_02_b Normalization and Correlation (5-22)/1 - 6 - 01_02_b Normalization and Correlation (522).mp4 6.8 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 3 - Getting Help (8_52).mp4 6.7 MB
- 6. Statistical Inference/03 - Third Week/05 - 09 01 Hypothesis testing (4-17)/3 - 5 - 09 01 Hypothesis testing (417).mp4 6.6 MB
- 9. Developing Data Products/01 - Week 1/07 - Shiny 5 Discussion (4-48)/2 - 7 - Shiny 5 Discussion (448).mp4 6.5 MB
- 3. Getting and Cleaning Data/04 - Week 4/03 - Regular Expressions II (8-00)/4 - 3 - Regular Expressions II (800).mp4 6.5 MB
- 2. R Programming/03 - Week 2/07 - Functions (part 1) [917]/3 - 7 - Functions (part 1) [917].mp4 6.5 MB
- 3. Getting and Cleaning Data/02 - Week 2/04 - Reading From APIs (7-57)/2 - 4 - Reading From APIs (757).mp4 6.4 MB
- 2. R Programming/03 - Week 2/11 - Scoping Rules - Optimization Example (OPTIONAL) [921]/3 - 11 - Scoping Rules - Optimization Example (OPTIONAL) [921].mp4 6.4 MB
- 9. Developing Data Products/01 - Week 1/11 - More advanced shiny, odds and ends (4-55)/2 - 11 - More advanced shiny, odds and ends (455).mp4 6.3 MB
- 6. Statistical Inference/05 - Extra lectures/01 - Just enough knitr to do the project/9 - 1 - Just enough knitr to do the project.mp4 6.2 MB
- 7. Regression Models/06 - Little extra videos/01 - Really, really quick intro to knitr/7 - 1 - Really, really quick intro to knitr.mp4 6.2 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 3 - Introduction to Git (4_49).mp4 6.2 MB
- 2. R Programming/04 - Week 3/05 - Loop Functions - split [909]/4 - 5 - Loop Functions - split [909].mp4 6.2 MB
- 4. Exploratory Data Analysis/02 - Week 1/10 - Graphics Devices in R (part 2) [731]/2 - 10 - Graphics Devices in R (part 2) [731].mp4 6.1 MB
- 6. Statistical Inference/01 - First Week/06 - 03 01 Conditional Probability (3-23)/1 - 6 - 03 01 Conditional Probability (323).mp4 6.1 MB
- 9. Developing Data Products/01 - Week 1/12 - Manipulate (4-49)/2 - 12 - Manipulate (449).mp4 6.1 MB
- 9. Developing Data Products/04 - Whole lectures/05 - Manipulate/5 - 5 - Manipulate.mp4 6.1 MB
- 5. Reproducible Research/02 - Week 2/07 - knitr (part 3) [446]/2 - 7 - knitr (part 3) [446].mp4 6.1 MB
- 2. R Programming/04 - Week 3/01 - Loop Functions - lapply [923]/4 - 1 - Loop Functions - lapply [923].mp4 6.1 MB
- 4. Exploratory Data Analysis/05 - Week 4/02 - Air Pollution Case Study [4035]/pm25_data.zip 6.1 MB
- 8. Practical Machine Learning/01 - Week 1/07 - Receiver Operating Characteristic (5-03)/1 - 7 - Receiver Operating Characteristic (503).mp4 6.1 MB
- 7. Regression Models/03 - Week 3/08 - 02_04_a Residuals (4-48)/3 - 8 - 02_04_a Residuals (448).mp4 6.0 MB
- 9. Developing Data Products/01 - Week 1/04 - Shiny 2 basic html and getting input (4-56)/2 - 4 - Shiny 2 basic html and getting input (456).mp4 6.0 MB
- 3. Getting and Cleaning Data/01 - Week 1/02 - Raw and Processed Data (7-07)/1 - 2 - Raw and Processed Data (707).mp4 5.9 MB
- 4. Exploratory Data Analysis/03 - Week 2/03 - ggplot2 (part 1) [626]/3 - 3 - ggplot2 (part 1) [626].mp4 5.9 MB
- 3. Getting and Cleaning Data/01 - Week 1/04 - Downloading Files (7-09)/1 - 4 - Downloading Files (709).mp4 5.9 MB
- 4. Exploratory Data Analysis/04 - Week 3/06 - Dimension Reduction (part 1) [755]/4 - 6 - Dimension Reduction (part 1) [755].mp4 5.9 MB
- 5. Reproducible Research/01 - Week 1/01 - Introduction/1 - 1 - Introduction.mp4 5.9 MB
- 2. R Programming/02 - Week 1/15 - Textual Data Formats [458]/2 - 15 - Textual Data Formats [458].mp4 5.9 MB
- 9. Developing Data Products/01 - Week 1/18 - shinyApps.io/2 - 18 - shinyApps.io.mp4 5.8 MB
- 9. Developing Data Products/01 - Week 1/14 - rCharts introduction (4-45)/2 - 14 - rCharts introduction (445).mp4 5.8 MB
- 2. R Programming/05 - Week 4/01 - The str Function [608]/5 - 1 - The str Function [608].mp4 5.8 MB
- 7. Regression Models/03 - Week 3/07 - 02_03_d Simulation examples finished (4-22)/3 - 7 - 02_03_d Simulation examples finished (422).mp4 5.8 MB
- 9. Developing Data Products/02 - Week 2/09 - RStudio Presenter 3 Discussion and comparison with Slidify (4-13)/3 - 9 - RStudio Presenter 3 Discussion and comparison with Slidify (413).mp4 5.7 MB
- 2. R Programming/03 - Week 2/10 - Scoping Rules - R Scoping Rules [834]/3 - 10 - Scoping Rules - R Scoping Rules [834].mp4 5.7 MB
- 3. Getting and Cleaning Data/03 - Week 3/07 - Merging Data (6-19)/3 - 7 - Merging Data (619).mp4 5.7 MB
- 6. Statistical Inference/02 - Second Week/04 - 05 04 Variance data example (3-33)/2 - 4 - 05 04 Variance data example (333).mp4 5.6 MB
- 5. Reproducible Research/03 - Week 3/06 - Evidence-based Data Analysis (part 1) [351]/EvidenceBasedDataAnalysis.pdf 5.6 MB
- 3. Getting and Cleaning Data/02 - Week 2/03 - Reading from The Web (6-47)/2 - 3 - Reading from The Web (647).mp4 5.6 MB
- 4. Exploratory Data Analysis/01 - Background Material/04 - Setting Your Working Directory (Windows)/1 - 4 - Setting Your Working Directory (Windows).mp4 5.6 MB
- 5. Reproducible Research/03 - Week 3/09 - Evidence-based Data Analysis (part 4) [447]/3 - 9 - Evidence-based Data Analysis (part 4) [447].mp4 5.5 MB
- 7. Regression Models/01 - Week 1/01 - 01_01_a Introduction to regression (4-10)/1 - 1 - 01_01_a Introduction to regression (410).mp4 5.5 MB
- 6. Statistical Inference/04 - Fourth Week/07 - 13 02 Bootstrapping example (3-29)/4 - 7 - 13 02 Bootstrapping example (329).mp4 5.5 MB
- 9. Developing Data Products/02 - Week 2/04 - Slidify customization (4-09)/3 - 4 - Slidify customization (409).mp4 5.5 MB
- 3. Getting and Cleaning Data/02 - Week 2/02 - Reading from HDF5 (6-45)/2 - 2 - Reading from HDF5 (645).mp4 5.5 MB
- 2. R Programming/03 - Week 2/05 - Control Structures - Repeat, Next, Break [457]/3 - 5 - Control Structures - Repeat, Next, Break [457].mp4 5.5 MB
- 4. Exploratory Data Analysis/04 - Week 3/10 - Working with Color in R Plots (part 2) [741]/4 - 10 - Working with Color in R Plots (part 2) [741].mp4 5.5 MB
- 9. Developing Data Products/01 - Week 1/10 - More advanced shiny, conditional execution of reactive statements (4-16)/2 - 10 - More advanced shiny, conditional execution of reactive statements (416).mp4 5.4 MB
- 4. Exploratory Data Analysis/02 - Week 1/07 - Base Plotting System (part 2) [656]/2 - 7 - Base Plotting System (part 2) [656].mp4 5.4 MB
- 5. Reproducible Research/02 - Week 2/06 - knitr (part 2) [411]/2 - 6 - knitr (part 2) [411].mp4 5.4 MB
- 8. Practical Machine Learning/04 - Week 4/04 - Unsupervised Prediction (4-24)/4 - 4 - Unsupervised Prediction (424).mp4 5.4 MB
- 2. R Programming/02 - Week 1/05 - Data Types - R Objects and Attributes [443]/2 - 5 - Data Types - R Objects and Attributes [443].mp4 5.4 MB
- 2. R Programming/04 - Week 3/08 - Debugging Tools - Using the Tools [821]/4 - 8 - Debugging Tools - Using the Tools [821].mp4 5.4 MB
- 4. Exploratory Data Analysis/04 - Week 3/03 - Hierarchical Clustering (part 3) [734]/4 - 3 - Hierarchical Clustering (part 3) [734].mp4 5.4 MB
- 2. R Programming/02 - Week 1/04 - R Console Input and Evaluation [446]/2 - 4 - R Console Input and Evaluation [446].mp4 5.3 MB
- 2. R Programming/05 - Week 4/02 - Simulation - Generating Random Numbers [747]/5 - 2 - Simulation - Generating Random Numbers [747].mp4 5.3 MB
- 6. Statistical Inference/01 - First Week/08 - 03 03 Independence (3-04)/1 - 8 - 03 03 Independence (304).mp4 5.3 MB
- 5. Reproducible Research/03 - Week 3/02 - RPubs [321]/3 - 2 - RPubs [321].mp4 5.2 MB
- 7. Regression Models/01 - Week 1/08 - 01_03_b Linear Least Squares Special Cases (4-22)/1 - 8 - 01_03_b Linear Least Squares Special Cases (422).mp4 5.2 MB
- 2. R Programming/02 - Week 1/18 - Subsetting - Lists/2 - 18 - Subsetting - Lists.mp4 5.2 MB
- 2. R Programming/02 - Week 1/16 - Connections Interfaces to the Outside World [435]/2 - 16 - Connections Interfaces to the Outside World [435].mp4 5.2 MB
- 2. R Programming/05 - Week 4/03 - Simulation - Simulating a Linear Model [431]/5 - 3 - Simulation - Simulating a Linear Model [431].mp4 5.2 MB
- 6. Statistical Inference/02 - Second Week/05 - 06 01 Binomial distrubtion (3-02)/2 - 5 - 06 01 Binomial distrubtion (302).mp4 5.2 MB
- 2. R Programming/01 - Background Material/01 - Installing R on Windows/1 - 1 - Installing R on Windows.mp4 5.1 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 13 - Installing R on Windows (3_20) {Roger Peng}.mp4 5.1 MB
- 6. Statistical Inference/03 - Third Week/02 - 08 02 T confidence intervals example (4-06)/3 - 2 - 08 02 T confidence intervals example (406).mp4 5.1 MB
- 2. R Programming/02 - Week 1/08 - Data Types - Factors [431]/2 - 8 - Data Types - Factors [431].mp4 5.1 MB
- 9. Developing Data Products/01 - Week 1/05 - Shiny 3 Creating a very basic prediction function (4-12)/2 - 5 - Shiny 3 Creating a very basic prediction function (412).mp4 5.1 MB
- 4. Exploratory Data Analysis/04 - Week 3/08 - Dimension Reduction (part 3) [642]/4 - 8 - Dimension Reduction (part 3) [642].mp4 5.1 MB
- 7. Regression Models/01 - Week 1/10 - 01_04_a Regression to the Mean (3-46)/1 - 10 - 01_04_a Regression to the Mean (346).mp4 5.0 MB
- 4. Exploratory Data Analysis/04 - Week 3/01 - Hierarchical Clustering (part 1) [721]/4 - 1 - Hierarchical Clustering (part 1) [721].mp4 5.0 MB
- 5. Reproducible Research/01 - Week 1/04 - Reproducible Research Concepts and Ideas (part 3) [326]/1 - 5 - Reproducible Research Concepts and Ideas (part 3) [326].mp4 5.0 MB
- 3. Getting and Cleaning Data/01 - Week 1/01 - Obtaining Data Motivation (5-38)/1 - 1 - Obtaining Data Motivation (538).mp4 5.0 MB
- 2. R Programming/04 - Week 3/02 - Loop Functions - apply [721]/4 - 2 - Loop Functions - apply [721].mp4 5.0 MB
- 4. Exploratory Data Analysis/03 - Week 2/02 - Lattice Plotting System (part 2) [612]/3 - 2 - Lattice Plotting System (part 2) [612].mp4 5.0 MB
- 3. Getting and Cleaning Data/03 - Week 3/01 - Subsetting and Sorting (6-51)/3 - 1 - Subsetting and Sorting (651).mp4 4.9 MB
- 4. Exploratory Data Analysis/03 - Week 2/01 - Lattice Plotting System (part 1) [622]/3 - 1 - Lattice Plotting System (part 1) [622].mp4 4.9 MB
- 2. R Programming/04 - Week 3/07 - Debugging Tools - Basic Tools [625]/4 - 7 - Debugging Tools - Basic Tools [625].mp4 4.9 MB
- 5. Reproducible Research/03 - Week 3/08 - Evidence-based Data Analysis (part 3) [425]/3 - 8 - Evidence-based Data Analysis (part 3) [425].mp4 4.9 MB
- 2. R Programming/03 - Week 2/08 - Functions (part 2) [713]/3 - 8 - Functions (part 2) [713].mp4 4.9 MB
- 2. R Programming/03 - Week 2/03 - Control Structures - For loops [425]/3 - 3 - Control Structures - For loops [425].mp4 4.8 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 5 - Creating a Github Repository (5_51).mp4 4.8 MB
- 7. Regression Models/03 - Week 3/05 - 02_03_b More simulation exercises (3-53)/3 - 5 - 02_03_b More simulation exercises (353).mp4 4.8 MB
- 4. Exploratory Data Analysis/02 - Week 1/09 - Graphics Devices in R (part 1) [534]/2 - 9 - Graphics Devices in R (part 1) [534].mp4 4.8 MB
- 6. Statistical Inference/03 - Third Week/04 - 08 04 A note on unequal variance (3-29)/3 - 4 - 08 04 A note on unequal variance (329).mp4 4.8 MB
- 4. Exploratory Data Analysis/04 - Week 3/11 - Working with Color in R Plots (part 3) [639]/4 - 11 - Working with Color in R Plots (part 3) [639].mp4 4.8 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 8 - Installing R Packages (5_37).mp4 4.8 MB
- 2. R Programming/02 - Week 1/17 - Subsetting - Basics/2 - 17 - Subsetting - Basics.mp4 4.7 MB
- 3. Getting and Cleaning Data/04 - Week 4/04 - Working with Dates (6-02)/4 - 4 - Working with Dates (602).mp4 4.7 MB
- 3. Getting and Cleaning Data/03 - Week 3/05 - Managing Data Frames with dplyr - Introduction/3 - 5 - Managing Data Frames with dplyr - Introduction.mp4 4.7 MB
- 1. The Data Scientist's Toolbox/Week 03/3 - 2 - What is Data_ (5_15).mp4 4.7 MB
- 3. Getting and Cleaning Data/01 - Week 1/08 - Reading JSON (5-03)/1 - 8 - Reading JSON (503).mp4 4.6 MB
- 5. Reproducible Research/03 - Week 3/06 - Evidence-based Data Analysis (part 1) [351]/3 - 6 - Evidence-based Data Analysis (part 1) [351].mp4 4.5 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 6 - Basic Git Commands (5_52).mp4 4.4 MB
- 2. R Programming/02 - Week 1/21 - Subsetting - Removing Missing Values/2 - 21 - Subsetting - Removing Missing Values.mp4 4.4 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 2 - The Data Scientist_'s Toolbox (5_09).mp4 4.4 MB
- 3. Getting and Cleaning Data/01 - Week 1/05 - Reading Local Files (4-55)/1 - 5 - Reading Local Files (455).mp4 4.4 MB
- 7. Regression Models/01 - Week 1/05 - 01_02_a Basic Notation and Background (3-26)/1 - 5 - 01_02_a Basic Notation and Background (326).mp4 4.3 MB
- 9. Developing Data Products/02 - Week 2/02 - Slidify intro (5-32)/slidify.pdf 4.2 MB
- 3. Getting and Cleaning Data/04 - Week 4/02 - Regular Expressions I (5-16)/4 - 2 - Regular Expressions I (516).mp4 4.1 MB
- 5. Reproducible Research/03 - Week 3/07 - Evidence-based Data Analysis (part 2) [334]/3 - 7 - Evidence-based Data Analysis (part 2) [334].mp4 4.1 MB
- 2. R Programming/02 - Week 1/01 - Introduction/2 - 1 - Introduction.mp4 4.1 MB
- 2. R Programming/01 - Background Material/02 - Installing R on a Mac/1 - 2 - Installing R on a Mac.mp4 4.0 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 14 - Install R on a Mac (2_02) {Roger Peng}.mp4 4.0 MB
- 4. Exploratory Data Analysis/02 - Week 1/01 - Introduction/2 - 1 - Introduction.mp4 4.0 MB
- 4. Exploratory Data Analysis/04 - Week 3/02 - Hierarchical Clustering (part 2) [524]/4 - 2 - Hierarchical Clustering (part 2) [524].mp4 4.0 MB
- 3. Getting and Cleaning Data/02 - Week 2/05 - Reading From Other Sources (4-44)/2 - 5 - Reading From Other Sources (444).mp4 3.9 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 4 - Finding Answers (4_35).mp4 3.8 MB
- 1. The Data Scientist's Toolbox/Week 03/3 - 3 - What About Big Data_ (4_15).mp4 3.8 MB
- 4. Exploratory Data Analysis/02 - Week 1/04 - Exploratory Graphs (part 2) [513]/2 - 4 - Exploratory Graphs (part 2) [513].mp4 3.8 MB
- 2. R Programming/03 - Week 2/04 - Control Structures - While loops [322]/3 - 4 - Control Structures - While loops [322].mp4 3.8 MB
- 2. R Programming/02 - Week 1/07 - Data Types - Matrices [324]/2 - 7 - Data Types - Matrices [324].mp4 3.7 MB
- 4. Exploratory Data Analysis/04 - Week 3/04 - K-Means Clustering (part 1) [546]/4 - 4 - K-Means Clustering (part 1) [546].mp4 3.7 MB
- 1. The Data Scientist's Toolbox/Week 03/03_04_experimentalDesign.pdf 3.7 MB
- 7. Regression Models/02 - Week 2/10 - 02_01_a Multivariate Regression (2-47)/2 - 10 - 02_01_a Multivariate Regression (247).mp4 3.7 MB
- 7. Regression Models/03 - Week 3/06 - 02_03_c More simulation examples 2 (2-52)/3 - 6 - 02_03_c More simulation examples 2 (252).mp4 3.6 MB
- 4. Exploratory Data Analysis/01 - Background Material/03 - Installing R Studio (Mac)/1 - 3 - Installing R Studio (Mac).mp4 3.5 MB
- 7. Regression Models/02 - Week 2/04 - 01_06_a Residuals (2-51)/2 - 4 - 01_06_a Residuals (251).mp4 3.5 MB
- 3. Getting and Cleaning Data/01 - Week 1/06 - Reading Excel Files (3-55)/1 - 6 - Reading Excel Files (355).mp4 3.5 MB
- 3. Getting and Cleaning Data/03 - Week 3/02 - Summarizing Data (11-37)/03_02_summarizingData.pdf 3.4 MB
- 9. Developing Data Products/01 - Week 1/02 - Motivating Shiny (1-49)/2 - 2 - Motivating Shiny (149).mp4 3.4 MB
- 9. Developing Data Products/02 - Week 2/03 - Slidify working it out (2-01)/3 - 3 - Slidify working it out (201).mp4 3.4 MB
- 3. Getting and Cleaning Data/01 - Week 1/07 - Reading XML (12-39)/01_07_readingXML.pdf 3.4 MB
- 6. Statistical Inference/01 - First Week/10 - 04 02 Expected values, simple examples (2-12)/1 - 10 - 04 02 Expected values, simple examples (212).mp4 3.3 MB
- 9. Developing Data Products/02 - Week 2/06 - Slidify reminder about knitting R (1-52)/3 - 6 - Slidify reminder about knitting R (152).mp4 3.3 MB
- 7. Regression Models/04 - Week 4/01 - 03_01_a Generalized Linear Models (2-32)/4 - 1 - 03_01_a Generalized Linear Models (232).mp4 3.3 MB
- 2. R Programming/04 - Week 3/03 - Loop Functions - mapply [446]/4 - 3 - Loop Functions - mapply [446].mp4 3.2 MB
- 6. Statistical Inference/02 - Second Week/02 - 05 02 Variance simulation examples (2-46)/2 - 2 - 05 02 Variance simulation examples (246).mp4 3.2 MB
- 2. R Programming/02 - Week 1/10 - Data Types - Data Frames [244]/2 - 10 - Data Types - Data Frames [244].mp4 3.2 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 4 - Introduction to Github (3_53).mp4 3.2 MB
- 9. Developing Data Products/01 - Week 1/06 - Shiny 4 Working with images (2-39)/2 - 6 - Shiny 4 Working with images (239).mp4 3.2 MB
- 2. R Programming/02 - Week 1/23 - Introduction to swirl/2 - 23 - Introduction to swirl.mp4 3.2 MB
- 2. R Programming/02 - Week 1/19 - Subsetting - Matrices/2 - 19 - Subsetting - Matrices.mp4 3.2 MB
- 3. Getting and Cleaning Data/04 - Week 4/05 - Data Resources (3-33)/4 - 5 - Data Resources (333).mp4 3.0 MB
- 2. R Programming/05 - Week 4/04 - Simulation - Random Sampling [237]/5 - 4 - Simulation - Random Sampling [237].mp4 3.0 MB
- 4. Exploratory Data Analysis/04 - Week 3/09 - Working with Color in R Plots (part 1) [408]/4 - 9 - Working with Color in R Plots (part 1) [408].mp4 3.0 MB
- 4. Exploratory Data Analysis/04 - Week 3/05 - K-Means Clustering (part 2) [426]/4 - 5 - K-Means Clustering (part 2) [426].mp4 2.9 MB
- 3. Getting and Cleaning Data/02 - Week 2/01 - Reading from MySQL (14-44)/02_01_readingMySQL.pdf 2.8 MB
- 4. Exploratory Data Analysis/04 - Week 3/12 - Working with Color in R Plots (part 4) [335]/4 - 12 - Working with Color in R Plots (part 4) [335].mp4 2.7 MB
- 1. The Data Scientist's Toolbox/Week 01/1 - 15 - Installing Rstudio (1_36) {Roger Peng}.mp4 2.6 MB
- 2. R Programming/01 - Background Material/03 - Installing R Studio (Mac)/1 - 3 - Installing R Studio (Mac).mp4 2.6 MB
- 1. The Data Scientist's Toolbox/Week 02/02_03_commandLineInterface.pdf 2.6 MB
- 3. Getting and Cleaning Data/04 - Week 4/01 - Editing Text Variables (10-46)/04_01_editingTextVariables.pdf 2.5 MB
- 2. R Programming/01 - Background Material/06 - Use R version 3.1.1/1 - 6 - Use R version 3.1.1.mp4 2.5 MB
- 2. R Programming/02 - Week 1/22 - Vectorized Operations [346]/2 - 22 - Vectorized Operations [346].mp4 2.5 MB
- 4. Exploratory Data Analysis/01 - Background Material/02 - Installing R on a Mac/1 - 2 - Installing R on a Mac.mp4 2.5 MB
- 2. R Programming/02 - Week 1/09 - Data Types - Missing Values [210]/2 - 9 - Data Types - Missing Values [210].mp4 2.4 MB
- 4. Exploratory Data Analysis/01 - Background Material/06 - Use R version 3.1.1/1 - 6 - Use R version 3.1.1.mp4 2.4 MB
- 3. Getting and Cleaning Data/04 - Week 4/03 - Regular Expressions II (8-00)/04_03_regularExpressionsII.pdf 2.3 MB
- 8. Practical Machine Learning/02 - Week 2/01 - Caret package (6-16)/010caretPackage.pdf 2.3 MB
- 1. The Data Scientist's Toolbox/Week 03/03_01_typesOfQuestions.pdf 2.2 MB
- 3. Getting and Cleaning Data/01 - Week 1/09 - The data.table Package (11-18)/01_09_dataTable.pdf 2.2 MB
- 1. The Data Scientist's Toolbox/Week 02/2 - 9 - Installing Rtools (2_29).mp4 2.2 MB
- 2. R Programming/04 - Week 3/04 - Loop Functions - tapply [317]/4 - 4 - Loop Functions - tapply [317].mp4 2.2 MB
- 8. Practical Machine Learning/01 - Week 1/01 - Prediction motivation (8-26)/001predictionMotivation.pdf 2.1 MB
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- 3. Getting and Cleaning Data/03 - Week 3/03 - Creating New Variables (10-32)/03_03_creatingNewVariables.pdf 2.1 MB
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