Greg Thatcher

Introduction to Python

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with numpy.

Introduction to R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

Intermediate Python

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

Python Data Science Toolbox (Part 1)

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

Supervised Learning with scikit-learn

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

Intermediate R

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.

Introduction to Importing Data in Python

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

Python Data Science Toolbox (Part 2)

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

Cleaning Data in Python

This course will equip you with all the skills you need to clean your data in Python.

Data Visualization with ggplot2 (Part 1)

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Intermediate Importing Data in Python

Improve your Python data importing skills and learn to work with web and API data.

Data Manipulation in R with dplyr

Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Cleaning Data in R

Learn to explore your data so you can properly clean and prepare it for analysis.

Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

Writing Functions in R

Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.

Introduction to Machine Learning

Learn to train and assess models performing common machine learning tasks such as classification and clustering.

Machine Learning with the Experts: School Budgets

Learn how to build a model to automatically classify items in a school budget.

Importing & Cleaning Data in R: Case Studies

In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

Linear Classifiers in Python

In this course you will learn the details of linear classifiers like logistic regression and SVM.

Exploratory Data Analysis in R: Case Study

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Time Series Analysis in R

Learn the core techniques necessary to extract meaningful insights from time series data.

Data Analysis in R, the data.table Way

Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Machine Learning Toolbox

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Intermediate R: Practice

Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.

Manipulating Time Series Data with xts and zoo in R

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

Credit Risk Modeling in R

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Statistical Modeling in R (Part 1)

This course was designed to get you up to speed with the most important and powerful methodologies in statistics.

Importing Data Into R

Learn how to parse data in any format. Whether it's flat files, statistics software, databases, or web data, you'll h...

Case Study: Exploring Baseball Pitching Data in R

Use a rich baseball dataset from the MLB's Statcast system to practice your data exploration skills.

Intro to Statistics with R: Introduction

A friendly introduction to fundamental concepts in statistics in R.

Kaggle R Tutorial on Machine Learning

Always wanted to compete in a Kaggle machine learning competition but not sure you have the right skillset? This inte...