Data, AI, and Cloud Courses

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

Master Amazon Redshifts SQL, data management, optimization, and security.

Take your dbt skills to the next level with this hands-on course designed for data engineers and analytics professionals.

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

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

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

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

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

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 to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

Learn how to transform and analyze data within your Microsoft Fabric account

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

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

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

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

Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.

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

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

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

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

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

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