Data, AI, and Cloud Courses

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

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.

Leverage the power of Python and PuLP to optimize supply chains.

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Learn how to approach and win competitions on Kaggle.

Analyze text data in R using the tidy framework.

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

Learn to build recommendation engines in Python using machine learning techniques.

In this course youll learn to use and present logistic regression models for making predictions.

Learn to design and run your own Monte Carlo simulations using Python!

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

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

Practice Power BI with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.

Learn how to identify, analyze, remove and impute missing data in Python.

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

Learn the core techniques necessary to extract meaningful insights from time series data.

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

Master Responsible AI Practices with this comprehensive course, featuring real-world case studies and interactive content.

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

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

In this course you will learn to fit hierarchical models with random effects.

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.