Data science courses

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Explore HR data analysis in Tableau with this case study.

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

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

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

Learn to analyze, plot, and model multivariate data.

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

Master Amazon Redshift's SQL, data management, optimization, and security.

Enhance your Tableau skills with this case study on inventory analysis. Analyze a dataset, create calculated fields, and create visualizations.

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

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

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

Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

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

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Learn to process sensitive information with privacy-preserving techniques.

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

In this course you'll learn how to apply machine learning in the HR domain.

Learn to create animated graphics and linked views entirely in R with plotly.

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

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Learn to solve real-world optimization problems using Python's SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Learn how to prepare and organize your data for predictive analytics.

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

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