Data, AI, and Cloud Courses

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.

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

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

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

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

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

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

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

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

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

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.

Learn to streamline your machine learning workflows with tidymodels.

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

Learn how to segment customers in Python.

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

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

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

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

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

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

Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.

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

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.

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 produce interactive web maps with ease using leaflet.

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

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

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