Data science courses

You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.

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

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.

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

Learn efficient techniques in pandas to optimize your Python code.

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

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

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

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

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

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

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

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

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

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

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

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

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

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

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

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

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

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

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!

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

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

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