Data science courses

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

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

Learn how to build a model to automatically classify items in a school budget.

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

Learn to process sensitive information with privacy-preserving techniques.

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

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

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

Learn to build pipelines that stand the test of time.

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

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

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

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

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

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

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Learn how to produce interactive web maps with ease using leaflet.

Boost your Excel skills with advanced referencing, lookup, and database functions using practical exercises.

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.