Michael Oberdorf

Introduction to Python

Master the basics of data analysis in Python. Expand your skill set 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 for Data Science

Level up your data science skills by creating visualizations using matplotlib and manipulating data frames 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.

pandas Foundations

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

Intermediate R

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

Deep Learning in Python

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

Supervised Learning with scikit-learn

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

Importing Data in Python (Part 1)

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

Cleaning Data in Python

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

Python Data Science Toolbox (Part 2)

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

Introduction to Data Visualization with Python

Learn more complex data visualization techniques using Matplotlib and Seaborn.

Statistical Thinking in Python (Part 1)

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

Importing Data in Python (Part 2)

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

Manipulating DataFrames with pandas

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

Data Manipulation in R with dplyr

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

Importing Data in R (Part 1)

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.

Cleaning Data in R

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

Natural Language Processing Fundamentals in Python

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

Network Analysis in Python (Part 1)

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

Merging DataFrames with pandas

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

Writing Functions in R

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

Unsupervised Learning in Python

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

Statistical Thinking in Python (Part 2)

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

Interactive Data Visualization with Bokeh

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

Machine Learning with the Experts: School Budgets

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

Importing Data in R (Part 2)

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

Joining Data in R with dplyr

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

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.

Introduction to 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.

Importing & 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.

Data Types for Data Science

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

Manipulating Time Series Data in Python

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

Visualizing Time Series Data in Python

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

Intro to Financial Concepts using Python

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

Network Analysis in Python (Part 2)

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 ...