Yao-Jen Kuo

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.

Intro to SQL for Data Science

Master the basics of querying tables in relational databases such as MySQL, Oracle, SQL Server, and PostgreSQL.

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.

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.

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collect...

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.

Data Visualization with ggplot2 (Part 1)

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

Importing Data in Python (Part 2)

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.

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.

Cleaning Data in R

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

Introduction to Data

Learn the language of data, study types, sampling strategies, and experimental design.

Correlation and Regression

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

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.

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.

Reporting with R Markdown

Learn to create interactive analyses and automated reports with R Markdown.

Joining Data in R with dplyr

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

Exploratory Data Analysis

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Data Visualization with ggplot2 (Part 2)

Take your data visualization skills to the next level with coordinates, facets, themes, and best practices in ggplot2.

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.

Machine Learning Toolbox

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

Unsupervised Learning in R

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Intermediate R - Practice

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

Data Visualization in R

This course provides a comprehensive introduction to working with base graphics in R.

Manipulating Time Series Data in R with xts & zoo

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.

Text Mining: Bag of Words

Learn the bag of words technique for text mining with R.

Exploratory Data Analysis in R: Case Study

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

Foundations of Inference

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Conda Essentials

Learn how to easily manage your software using conda.

Introduction to Portfolio Analysis in R

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

String Manipulation in R with stringr

Learn how to pull character strings apart, put them back together and use the stringr package.

Data Visualization with ggplot2 (Part 3)

This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Financial Trading in R

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Data Visualization in R with ggvis

Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

Object-Oriented Programming in R: S3 and R6

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

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...

Data Analysis and Statistical Inference

This interactive DataCamp course complements the Coursera course Data Analysis and Statistical Inference by Mine Çeti...

How to work with Quandl in R

Quandl offers millions of free and open financial, economic, and social datasets. In this tutorial you will learn how...

Kaggle Python Tutorial on Machine Learning

Always wanted to compete in a Kaggle competition but not sure you have the right skillset? This interactive tutorial ...

R 語言導論

我們將在 R 語言導論學習這個熱門的開源軟體，包含因素向量、清單與資料框等資料類別。 透過這門課的內容我們就可以著手對資料做分析。 目前 R 語言在全球已經有超過兩百萬個使用者，且人數以年增率 40% 高速成長中。 隨著日益增多的學術...