Instructor Logistics
Patrick Boily, Data Action Lab & Idlewyld Analytics
       Linked In profile
       pat.boily@data-action-lab.com
       idlewyld@idlewyld.net
       Follow @idlewyld_IACS on Twitter (#iqc4376) for DV content

 Schedule:
       01. Data Fundamentals (07-Oct, 10am-noon)
       02. Overview of Anomaly Detection and Outlier Analysis (14-Oct, 10am-noon)
       03. Basics of Programming (28-Oct, 10am-noon)
       04. Programming in R (and Python) (04-Nov, 10am-noon)
       05. Data Processing (11-Nov, 10am-noon)
       06. Quantitative Anomaly Detection Methods (18-Nov, 10am-noon)
       07. Quantitative Anomaly Detection Methods (25-Nov, 10am-noon)
       08. Outlier Ensembles (02-Dec, 10am-noon)
       09. Anomaly Detection in Text Datasets (09-Dec, 1pm-3pm)
       10. Anomaly Detection in High-Dimensional Datasets (16-Dec, 10am-noon)
       11. Clustering and K-Means (13-Jan, 10am-noon)
       12. Advanced Clustering Topics (20-Dec, 10am-noon)

Zoom link (please register for an account prior to the start of the course.
Course Materials Datasets and Examples
Slide Decks:
       Data Fundamentals
       Introduction to Programming
       Programming in R (and Python)
       Data Processing

       Overview of Anomaly Detection and Outlier Analysis
       Quantitative Anomaly Detection Methods
       Qualitative Anomaly Detection Methods
       Outlier Ensembles
       Anomaly Detection in Text Datasets
       Anomaly Detection in High-Dimensional Datasets

       Clustering and Advanced Topics

Supplementary Materials:
      Basics of R for Data Analysis (Report)
      Basics of R (Videos) [part I, part II]
      R Basics (Notebook)
      More Data Stuff in R (Notebook)

      The Essentials of Data Preparation (Report)
      Data Wrangling and the Tidyverse (Notebook)
      Data Cleaning and Preparation in R (Notebook)

      Anomaly Detection and Outlier Analysis (Report)
      R Code Archive for the Slides (not commented)

R and R Studio (recommended):
      R Studio download link and support documentation
      R download link and support documentation

Python and Anaconda (optional):
      Anaconda download link and support documentation

Distracted Driving Fatalities
flights1_2019_1
Flights Read Me
Flights Read Me

tb.csv
pollution.csv
cases.csv
car.csv
cities.txt
Algae_Blooms