Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Learn how to tune your model's hyperparameters to get the best predictive results.

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

In this course you'll learn how to use data science for several common marketing tasks.

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn how to visualize big data in R using ggplot2 and trelliscopejs.

Use survival analysis to work with time-to-event data and predict survival time.

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.

Are you curious about the inner workings of the models that are behind products like Google Translate?

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.