Data, AI, and Cloud Courses

Visualize seasonality, trends and other patterns in your time series data.

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

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

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

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

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

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

Explore ways to work with date and time data in SQL Server for time series analysis

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

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

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

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

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

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

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

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

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

Analyze text data in R using the tidy framework.

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

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

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

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

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

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

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

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

Learn how to approach and win competitions on Kaggle.

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

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

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.