R Course

Lessons
announcements*

Previous Chapter:

none

Previous Lesson:

Play

Next Lesson:

Next Chapter:

Welcome to The Infinite Actuary’s R Course Blog

Sat, 05 Jan 2019

I will be posting updates to the course on this blog. Thanks for joining in. I hope you are learning a lot about R and beginning to gain confidence to use it for all sorts of analysis. Don’t forget: The R course is on sale until Saturday, January 5th. Recent Updates to the R Course: […]

About the R Course ... lessons ... min of video
- What is the R Course? ...
  - Introduction to the R Course (2:17)
  - R Course Overview Document (handout)
A. R Foundational Knowledge ... lessons ... min of video
- A.1. R Foundations Lectures ...
  - A.1.1. Install R and R Studio (sample) (3:01)
  - A.1.2. R Studio Overview (3:24)
  - A.1.3. R Vectors (8:43)
  - A.1.4. R Data Types (6:10)
  - A.1.5. Sequence and Repetition (7:49)
  - A.1.6. Vector Operations (4:13)
  - A.1.7. Introduction to Matrices in R (2:40)
  - A.1.8. R Matrices Part 1 (5:38)
  - A.1.9. R Matrices Part 2 (4:46)
  - A.1.10. Download the zip containing the CSV file for the following data frame lectures (A.1.11 to A.1.13) (handout)
  - A.1.11. Introduction to Data Frames (7:06)
  - A.1.12. Subsetting and filtering data frames (7:14)
  - A.1.13. Adding and deleting columns in a data frame (2:48)
  - A.1.14 Download the Base R Cheat Sheet (handout)
- A.2. R Foundations - Actuarial Project ...
  - A.2.0 Download the instructions for the R Foundations R Actuarial Project (handout)
  - A.2.1. R Foundations Actuarial Project Video Solution (4:29)
B. Data Cleanup using R ... lessons ... min of video
- B.1. Data Cleanup using R -- Lectures ...
  - B.1.0. Download the CSV for the R Data Cleanup Lectures (handout)
  - B.1.1. Reading in the Data Cleanup CSV file into R (3:57)
  - B.1.2. Initial Data Frame Adjustments (2:47)
  - B.1.3. Replacing Missing Data with Known Data (2:57)
  - B.1.4. Adding in a Column with Known Amounts (3:20)
  - B.1.5. Replacing missing data with average and median (imputing) (6:27)
  - B.1.6. Reading in data and handling missing values (2:14)
  - B.1.7. Filter data using which (4:00)
  - B.1.8. Filtering data by complete cases (1:52)
  - B.1.9. Impute methods while handling missing data (6:25)
  - B.1.10. Replacing data using gsub (3:34)
- B.2. Data Cleanup using R -- Actuarial Project ...
  - B.2.0.0. Download the zip file for the Data Cleanup Actuarial Project (handout)
  - B.2.0.1. Introduction to the R Course Actuarial Project on Data Cleanup (sample) (3:45)
  - B.2.1. Video Solution Task 1 (3:32)
  - B.2.2. Video Solution Task 2 (1:45)
  - B.2.3. Video Solution Task 3 (2:19)
  - B.2.4. Video Solution Task 4 (5:23)
  - B.2.5. Video Solution Task 5 (3:58)
  - B.2.6. Video Solution Task 6 (9:22)
  - B.2.7. Video Solution Task 7 (5:47)
C. Data Visualization and Exploratory Analysis using R ... lessons ... min of video
- C.1. Data Visualization and Exploratory Analysis using R -- Lectures ...
  - C.1.1 Installing R visualization packages (2:50)
  - C.1.2. Quick discussion on qplot (3:36)
  - C.1.3. GGPLOT2 Scatterplot introduction (6:04)
  - C.1.4. Changing the color and size in ggplot (4:47)
  - C.1.5. Adding labels, title, and prediction equation to your ggplot visualization (6:37)
  - C.1.6. Making your visualization outstanding using Facets (3:40)
  - C.1.7. Creating histograms in ggplot (3:26)
  - C.1.8. Creating Density charts in ggplot (1:08)
  - C.1.9. Using R to create long data from wide data via the Tidy way (6:47)
  - C.1.10. Bar Charts Horizontal and Vertical (1:41)
  - C.1.11. GGPLOT Box Plot with the AMAZING Feature (sample) (4:10)
  - C.1.12. Adjusting your Theme (3:47)
  - C.1.13 Download the GGPLOT2 Rstudio Cheat Sheet (handout)
- C.2. Data Visualization and Exploratory Analysis using R -- Actuarial Project ...
D. Predictive Analytics using R ... lessons ... min of video
- D.1. Machine Learning for Actuaries -- Lectures ...
  - D.1.0.0. Download the Machine Learning Lecture Datasets (handout)
  - D.1.1. Introduction to Machine Learning for Actuaries (2:31)
  - D.1.2. Partitioning Your Dataset for Model Building (3:26)
  - D.1.3. Simple Linear Regression -- Part 1 (2:05)
  - D.1.4. Simple Linear Regression -- Part 2 (5:20)
  - D.1.5. Simple Linear Regression -- Part 3 (4:14)
  - D.1.6. Simple Linear Regression -- Part 4 (2:42)
  - D.1.7. Multiple Linear Regression -- Part 1 (1:23)
  - D.1.8. Multiple Linear Regression -- Part 2 (3:27)
  - D.1.9. Multiple Linear Regression -- Part 3 (3:49)
  - D.1.10. Stepwise Linear Regression (3:06)
  - D.1.11. Polynomial Regression (2:09)
  - D.1.12. Logistic Regression Generalized Linear Model (GLM) -- Part 1 (3:57)
  - D.1.13. Logistic Regression Generalized Linear Model (GLM) -- Part 2 (6:13)
  - D.1.14. Logistic Regression Generalized Linear Model (GLM) -- Part 3 (1:45)
  - D.1.15. Logistic Regression Generalized Linear Model (GLM) -- Part 4 (5:29)
- D.2. Machine Learning for Actuaries -- Actuarial Project ...
  - D.2.0.0 Download the Machine Learning Actuarial Project Project Files (handout)
  - D.2.0.1. Introduction to the Machine Learning Actuarial Project (3:35)
  - D.2.1 Video Solution Task 1 (3:05)
  - D.2.2. Video Solution Task 2 (3:54)
  - D.2.3. Video Solution Task 3 (2:13)
  - D.2.4. Video Solution Task 4 (1:58)
  - D.2.5. Video Solution Task 5 (7:10)
- D.3. Further Predictive Modeling in R -- Decision Trees and Random Forests ...
  - D.3.1. Introduction to Data Partition via CARET package (5:02)
  - D.3.2. Download the dataset needed for this set of lectures (handout)
  - D.3.3. Discuss the dataset, data dictionary, and what we are trying to predict (2:49)
  - D.3.4. Import the annuities dataset into R, load packages, cleanup data structure (7:34)
  - D.3.5. Exploratory data analysis, create new variables (11:11)
  - D.3.6. Data partition in R via CARET (4:42)
  - D.3.7. Introduction to Decision Trees (12:09)
  - D.3.8.1. Decision Trees Predictive Modeling in R -- Part 1 (6:45)
  - D.3.8.2. Decision Trees Predictive Modeling in R -- Part 2 (6:15)
  - D.3.8.3. Decision Trees Predictive Modeling in R -- Part 3 (5:54)
  - D.3.9. Introduction to Random Forests (9:06)
  - D.3.10.1. Random Forest predictive modeling in R -- Part 1 Method 1 (5:00)
  - D.3.10.2. Random Forest Predictive Modeling in R -- Part 2 Method 2 (6:43)
E. Communicating Results in R ... lessons ... min of video
- E.1. R Markdown ...
  - E.1.1. Introduction to R Markdown (4:08)
  - E.1.2. Creating R Markdown file, editing, and output (9:47)
  - E.1.3 Download the R Markdown Cheat Sheet (handout)
F. R Actuarial Capstone Project (From Raw Datasets to Predictive Model) ... lessons ... min of video
- F.1. Catastrophic Event Survival Analysis ...
  - F.1.0. Introduction to the R Capstone Actuarial Project (7:44)
  - F.1.1. Kaggle, Home of Data Science, Tour (6:08)
  - F.1.2. Download the Capstone Project datasets (handout)
  - F.1.3. Load data (7:14)
  - F.1.4. Data Cleanup Part 1 (7:54)
  - F.1.5. Data Cleanup Part 2 (5:52)
  - F.1.6. Data Cleanup Part 3 (8:00)
  - F.1.7. Data Cleanup Part 4 with Data Viz (12:45)
  - F.1.8. Create Predictive Model, Apply Predictions, Submit Predictions (8:22)
  - F.1.9. Create your own Kaggle Kernal (6:43)
  - F.1.10. Download dataset for the Actuarial Life Insurance Application (handout)
  - F.1.11. Actuarial Life Insurance Application -- Part 1 (6:58)
  - F.1.12. Actuarial Life Insurance Application -- Part 2 (8:41)

Select your preference for the video player:

Select your preference for viewing TIA forums

Select your color preference for the study page

R Course