Data, AI, and Cloud Courses

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

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

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

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

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

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

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

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

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

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

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.

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.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

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

Learn how to use FastAPI to develop APIs that support AI models, built to meet real-world demands.

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

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 analyze, plot, and model multivariate data.

In this course youll learn how to apply machine learning in the HR domain.

Learn essential finance math skills with practical Excel exercises and real-world examples.

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

Learn the fundamentals of valuing stocks.

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Learn how to tune your models hyperparameters to get the best predictive results.

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.

Learn to use the Bioconductor package limma for differential gene expression analysis.

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

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

In this course youll learn how to leverage statistical techniques for working with categorical data.