Introduction to Python Introduction to R Intermediate Python Introduction to Data Literacy Joining Data in R with dplyr Building Web Applications in R with Shiny Introduction to Importing Data in R Supervised Learning in R: Regression Unsupervised Learning in R Working with Data in the Tidyverse Machine Learning with caret in R Working with the RStudio IDE (Part 2) Tree-Based Models in R Case Study: Exploratory Data Analysis in R Visualizing Geospatial Data in R Joining Data with data.table in R Data Manipulation with data.table in R Text Mining with Bag-of-Words in R Support Vector Machines in R Creating Dashboards with shinydashboard Case Study: Analyzing City Time Series Data in R Visualizing Big Data with Trelliscope in R Creating R Packages Intermediate Statistical Modeling in R Data Analysis and Statistical Inference Intro to Statistics with R: Repeated measures ANOVA DataCamp Course Completions Python Data Science Toolbox (Part 1) Intermediate R Introduction to the Tidyverse Data Manipulation in R with dplyr Intermediate SQL Queries Data Storytelling Concepts Intermediate R: Practice Data Types for Data Science in Python Modeling with Data in the Tidyverse Introduction to Version Control with Git Hierarchical and Mixed Effects Models in R ARIMA Models in R Data Visualization with ggplot2 (Part 3) Linear Algebra for Data Science in R Visualizing Time Series Data in R Multiple and Logistic Regression in R Introduction to Statistical Modeling in R Spatial Analysis with sf and raster in R String Manipulation with stringr in R Case Studies: Building Web Applications with Shiny in R Foundations of Functional Programming with purrr Building Dashboards with flexdashboard Intermediate Interactive Data Visualization with plotly in R Optimizing R Code with Rcpp Intro to Statistics with R: Introduction Intro to Statistics with R: Correlation and Linear Regression Python Data Science Toolbox (Part 2) Introduction to Data Science in Python Writing Functions in R Data Visualization in R Data Visualization with ggplot2 (Part 1) Artificial Intelligence (AI) Concepts in Python Data Analysis in R, the data.table Way Data Visualization with ggplot2 (Part 2) Writing Efficient R Code Intermediate Importing Data in R Time Series Analysis in R Dealing With Missing Data in R Data Visualization in R with ggvis Foundations of Probability in R Working with Dates and Times in R Communicating with Data in the Tidyverse Object-Oriented Programming with S3 and R6 in R Importing Data Into R Machine Learning in the Tidyverse Interactive Data Visualization with rbokeh Categorical Data in the Tidyverse Parallel Computing in R Intermediate Functional Programming with purrr Defensive R Programming Intro to Statistics with R: Student's T-test Intro to Statistics with R: Multiple Regression Reporting with R Markdown Cleaning Data in R Introduction to Data in R Exploratory Data Analysis in R Introduction to Machine Learning Supervised Learning in R: Classification Working with the RStudio IDE (Part 1) Correlation and Regression in R Foundations of Inference in R Interactive Data Visualization with plotly in R R for SAS, SPSS and STATA Users Forecasting in R Generalized Linear Models in R Importing & Cleaning Data in R: Case Studies Visualization Best Practices in R Manipulating Time Series Data with xts and zoo in R Survival Analysis in R Interactive Maps with leaflet in R Nonlinear Modeling with Generalized Additive Models (GAMs) in R Introduction to Spark with sparklyr in R Intermediate Regular Expressions in R Scalable Data Processing in R Data Visualization with lattice in R Intro to Statistics with R: Analysis of Variance (ANOVA) Intro to Statistics with R: Moderation and Mediation