Datacamp

Many times in machine learning, the goal is to find patterns in data without trying to make predictions. This is called unsupervised learning. One common use case of unsupervised learning is grouping consumers based on...

Once you've started learning tools for data manipulation and visualization like dplyr and ggplot2, this course gives you a chance to use them in action on a real dataset. You'll explore the historical voting of...

Proper data modeling is the foundation of data analysis and creating reports in Power BI. This course lets you explore a toolbox of data cleaning, shaping, and loading techniques, which you can apply to your...

In this finance-oriented introduction to R, you will learn essential data structures such as lists and data frames and have the chance to apply that knowledge to real-world financial examples. By the end of the...

Images are everywhere! We live in a time where images contain lots of information, which is sometimes difficult to obtain. This is why image pre-processing has become a highly valuable skill, applicable in many use...

Neural networks have been at the forefront of Artificial Intelligence research during the last few years, and have provided solutions to many difficult problems like image classification, language translation or Alpha Go. PyTorch is one...

The beauty of R is that it is built for performing data analysis. The downside is that sometimes R can be slow, thereby obstructing our analysis. For this reason, it is essential to become familiar...

Are you ready to apply your Tableau skills to a real-world dataset? For subscription-based businesses, reducing customer churn is a top priority. In this Tableau case study, you'll investigate a dataset from an example telecom...

Shiny is an R package that makes it easy to build highly interactive web apps directly in R. Using Shiny, data scientists can create interactive web apps that allow your team to dive in and...

Machine learning models are easier to implement now more than ever before. Without proper validation, the results of running new data through a model might not be as accurate as expected. Model validation allows analysts...

This course will introduce the key elements of machine learning to the business leaders. We will focus on the key insights and base practices how to structure business questions as modeling projects with the machine...

In this course, you will take a deeper dive into the wide range of data formats out there. More specifically, you'll learn how to import data from relational databases and how to import and work...

In this course, you'll learn how to use statistical techniques to make inferences and estimations using numerical data. This course uses two approaches to these common tasks. The first makes use of bootstrapping and permutation...

Data scientists can experience huge benefits by learning concepts from the field of software engineering, allowing them to more easily reutilize their code and share it with collaborators. In this course, you'll learn all about...

Deep learning is here to stay! It's the go-to technique to solve complex problems that arise with unstructured data and an incredible tool for innovation. Keras is one of the frameworks that make it easier...

Bash is a concise, superfast, and robust scripting language for data and file manipulation. It’s a vital skill for building analytics pipelines in the cloud, favored by Linux users to work with data stored across...

Time series data is ubiquitous. Whether it be stock market fluctuations, sensor data recording climate change, or activity in the brain, any signal that changes over time can be described as a time series. Machine...

Cluster analysis is a powerful toolkit in the data science workbench. It is used to find groups of observations (clusters) that share similar characteristics. These similarities can inform all kinds of business decisions; for example,...

Being able to understand, use, and summarize non-numerical data—such as a person’s blood type or marital status—is a vital component of being a data scientist. In this course, you’ll learn how to manipulate and visualize...

Dates and times are abundant in data and essential for answering questions that start with when, how long, or how often. However, they can be tricky, as they come in a variety of formats and...