For students of Harvard CSCI E-96 Data Mining for Business
Fall 2024 University syllabus or PDF here
Spring 2024 University syllabus or PDF here
If you are new to R, please take an online course to get familarity prior to the first session. We will still cover R basics but students have been aided by spending a few hours taking a free online course at Youtube or DataCamp. The code below should be run in the console to install packages needed for the semester.
If you encounter any errors don't worry we will find time to work through them. The qdap library is usually the trickiest because it requires Java and rJava and does not work on Mac. So if you get any errors, try removing that from the code below and rerunning. This will take a long time if you don't already have the packages, so please run prior to class, and at a time you don't need your computer ie at night.
# Individually you can use
# install.packages('packageName') such as below:
install.packages('ggplot2')
# or
install.packages('pacman')
pacman::p_load(ggplot2, ggthemes, ggdark, rbokeh, maps,
ggmap, leaflet, radiant.data, DataExplorer,
vtreat, dplyr, ModelMetrics, pROC,
MLmetrics, caret, e1071, plyr,
rpart.plot, randomForest, forecast, dygraphs,
lubridate, jsonlite, tseries, ggseas,
arules,fst, recommenderlab,reshape2,
TTR,quantmod, htmltools,
PerformanceAnalytics,rpart, data.table,
pbapply, rbokeh, stringi, tm, qdap, readr,
dendextend, wordcloud, RColorBrewer,
tidytext, radarchart, RCurl, openNLP, xml2, stringr,
devtools, flexdashboard, rmarkdown, httr)
This is tentative and subject to change to maximize learning
| Date | Topic |
|---|---|
| Sept 9 | Intro to R, R-studio & git |
| Sept 16 | Intro to Data Mining |
| Sept 23 | More R Practice & EDA |
| Sept 30 | Data mining workflows |
| Oct 7 | Regression & Log Regression |
| Oct 14 | no class (university holiday) |
| Oct 21 | Decision Tree & Random Forest |
| Oct 28 | Time Series Data |
| Nov 4 | Equities |
| Nov 11 | Predicting Risk & non-traditional investing |
| Nov 18 | Text analysis & NLP |
| Nov 25 | Text analysis & NLP, continued |
| Dec 2 | Chat GPT basics |
| Dec 9 | Responsible AI & tech ethics |
| Dec 16 | Optional Class Lab |
| Date | Topic |
|---|---|
| Jan 27 | Intro to R, R-studio & git |
| Feb 3 | Intro to Data Mining |
| Feb 10 | Chat GPT basics |
| Feb 17 | No class - President's Day |
| Feb 24 | More R Practice & EDA |
| Mar 3 | Data mining workflows |
| Mar 10 | Regression & Log Regression |
| Mar 17 | No class - Spring Break |
| Mar 24 | Decision Tree & Random Forest |
| Mar 31 | Time Series Data |
| Apr 7 | Equities |
| Apr 14 | Predicting Risk & non-traditional investing |
| Apr 21 | Text analysis & NLP |
| Apr 28 | Text analysis & NLP, continued |
| May 5 | APIs, Novel & Advanced LLM workflows |
| May 12 | Responsible AI & tech ethics |