Datacamp

This course will teach you to leverage the tools in the "tidyverse" to generate, explore, and evaluate machine learning models. Using a combination of tidyr and purrr packages, you will build a foundation for how...

This course will introduce a powerful classifier, the support vector machine (SVM) using an intuitive, visual approach. Support Vector Machines in R will help students develop an understanding of the SVM model as a classifier...

As with any fundamentals course, Introduction to Natural Language Processing in R is designed to equip you with the necessary tools to begin your adventures in analyzing text. Natural language processing (NLP) is a constantly...

A loan amortization schedule sounds like something that's only used by bankers and financial traders, right? Wrong! In this course, we'll be looking at the key financial formulas in Google Sheets that you can use...

Data is all around us and can help us to understand many things. Making a pretty graph is great, but how can we tell the difference between a few outliers on a graph and a...

For many machine learning problems, simply running a model out-of-the-box and getting a prediction is not enough; you want the best model with the most accurate prediction. One way to perfect your model is with...

Sampling in Python is the cornerstone of inference statistics and hypothesis testing. It's a powerful skill used in survey analysis and experimental design to draw conclusions without surveying an entire population. In this Sampling in...

With an increasing amount of data and more complex algorithms available to scientists and practitioners today, parallel processing is almost always a must, and in fact, is expected in packages implementing time-consuming methods. This course...

Deploying machine learning models in production seems easy with modern tools, but often ends in disappointment as the model performs worse in production than in development. This course will give you four superpowers that will...

Experimental design is a crucial part of data analysis in any field, whether you work in business, health or tech. If you want to use data to answer a question, you need to design an...

Most of the useful data in the world, from economic data to news content to geographic information, lives somewhere on the internet - and this course will teach you how to access it. You'll explore...

The real world is messy and your job is to make sense of it. Toy datasets like MTCars and Iris are the result of careful curation and cleaning, even so the data needs to be...

Losing time on slow queries? Hesitant to share your queries with more seasoned coworkers? In this course, you will learn how to structure your PostgreSQL to run in a fraction of the time. Exploring intertwined...

We learn to speak far before we learn to read. Even in the digital age, our main method of communication is speech. Spoken Language Processing with Python will help you load, transform and transcribe audio...

If you surveyed a large number of data scientists and data analysts about which tasks are most common in their workday, cleaning data would likely be in almost all responses. This is the case because...

As the saying goes, “A chart is worth a thousand words”. This is why visualization is the most used and powerful way to get a better understanding of your data. After this course you will...

If you've ever done anything with financial or economic time series, you know the data come in various shapes, sizes, and periodicities. Getting the data into R can be stressful and time-consuming, especially when you...

The world is full of unobservable variables that can't be directly measured. You might be interested in a construct such as math ability, personality traits, or workplace climate. When investigating constructs like these, it's critically...

Communication is a key part of the data science process. Dashboards are a popular way to present data in a cohesive visual display. In this course you'll learn how to assemble your results into a...

Volatility is an essential concept in finance, which is why GARCH models in Python are a popular choice for forecasting changes in variance, specifically when working with time-series data that are time-dependant. This course will...