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

Learn to easily summarize and manipulate lists using the purrr package.

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

In this course you'll learn how to create static and interactive dashboards using flexdashboard and shiny.

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

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

Use RNNs to classify text sentiment, generate sentences, and translate text between languages.

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Learn efficient techniques in pandas to optimize your Python code.

Learn to load, transform, and transcribe human speech from raw audio files in Python.

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.