Data, AI, and Cloud Courses

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

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

Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.

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

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

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

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

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

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

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

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

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

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

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

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.

Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

Learn how to work with streaming data using serverless technologies on AWS.

Learn how to efficiently collect and download data from any website using R.

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

Learn the most important functions for manipulating, processing, and transforming data in SQL Server.

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