Michael Oberdorf

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.

Python Data Science Toolbox (Part 2)

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

Statistical Thinking in Python (Part 1)

Build the foundation you need to think statistically and to speak the language of your data.

Merging DataFrames with pandas

This course is all about the act of combining, or merging, DataFrames, an essential part your Data Scientist's toolbox.

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.

Introduction to Deep Learning in Python

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

pandas Foundations

Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

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.

Unsupervised Learning in Python

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

Introduction to Data Visualization in Python

Learn complex data visualization techniques using Matplotlib and seaborn.

Statistical Thinking in Python (Part 2)

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Introduction to Natural Language Processing in Python

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from ...

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 Importing Data in R

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Introduction to Databases in Python

In this course, you'll learn the basics of relational databases and how to interact with them.

Data Types for Data Science in Python

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them t...

Cleaning Data in R

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

Case Study: School Budgeting with Machine Learning i...

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

Manipulating DataFrames with pandas

You will learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.

Cleaning Data in Python

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

Joining Data in R with dplyr

This course will show you how to combine data sets with dplyr's two table verbs.

Manipulating Time Series Data in Python

In this course you'll learn the basics of working with time series data.

Intermediate Importing Data in R

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

Time Series Analysis in Python

In this course you'll learn the basics of analyzing time series data.

Intermediate R: Practice

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

Interactive Data Visualization with Bokeh

Learn how to create versatile and interactive data visualizations using Bokeh.

Introduction to Network Analysis in Python

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Importing and Managing Financial Data in Python

In this course, you'll learn how to import and manage financial data in Python using various tools and sources.

Introduction to Financial Concepts in Python

Using Python and NumPy, learn the most fundamental financial concepts.

Visualizing Time Series Data in Python

Visualize seasonality, trends and other patterns in your time series data.

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.

Intermediate Network Analysis in Python

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Einführung in R

In dieser Einführung in R werden Sie die Grundlagen der wunderbaren Open-Source-Sprache, inklusive der Faktoren, der ...