Data science courses

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Learn how to use Python to analyze customer churn and build a model to predict it.

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

Develop the skills you need to clean raw data and transform it into accurate insights.

Learn efficient techniques in pandas to optimize your Python code.

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Learn how to write recursive queries and query hierarchical data structures.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

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

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Learn to use the Census API to work with demographic and socioeconomic data.

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.

Learn how to design and implement triggers in SQL Server using real-world examples.

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.