DATA 413/613 Data Science

Syllabus

Lectures

• 01 Git and the Terminal
  • 01 The Terminal and Bash Basics.
  • 01 Git Setup.
  • 01 Git and GitHub.
  • 01 Git Large File Storage.
  • 01 A Quick Introduction to Git and GitHub.
  • 01 Lab: Review of Tidyverse Concepts.
• 02 Organization
  • 02 File Structure
  • 02 Project Structure
  • 02 Project Management
• 03 Vectors and Iteration
  • 03 Vectors.
  • 03 Subsetting.
  • 03 Functions.
  • 03 Iteration.
  • 03 Lab.
• 04 R Packages
  • 04 R Packages.
  • 04 Unit Testing.
  • 04 Automated Checks.
  • 04 Style.
• 05 Web Scraping
  • 05 APIs.
  • 05 Web Scraping.
  • 05 Lab.
• 06 Introduction to Python
  • 06 Python Setup and Reticulate.
  • 06 Numpy.
  • 06 Pandas.
  • 06 Seaborn.
  • 06 Seaborn.objects.
• 07 Introduction to SQL
  • 07 SQL.
  • 07 DBeaver.
• 08 GNU Make
  • 08 GNU Make.
  • 08 Penguins Exercise.
  • 08 Very Basic Makefile Example.
• 09 Shiny Apps
  • 09 Shiny Basics.
  • 09 Layouts.
  • 09 Reactivity.
  • 09 HTML.
  • 09 File Uploads.
  • 09 Shiny Lab 1: World Bank Data.
  • 09 Shiny Lab 2: Cereals Data.

Extra Lectures

• A1 Basic Statistics
  • A1 Basic Statistics.
  • A1 Statistical Tests, P-values, Confidence Intervals, and Power: A Guide to Misinterpretations.
  • A1 Lab.
• A2 Linear Models
  • A2 Simple Linear Regression.
  • A2 Many Models.
  • A2 Lab.
• A3 Data.table
  • A3 Manipulating Large(ish) Datasets with data.table.
  • A3 Lab.
• A4 Dates and Times
  • A4 Dates.
  • A4 Lab.