Data, AI, and Cloud Courses

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

In this course, youll learn how to import and manage financial data in Python using various tools and sources.

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

Practice data storytelling using real-world examples! Communicate complex insights effectively with a dataset of certified green businesses.

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

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

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

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

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

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

Learn how to approach and win competitions on Kaggle.

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

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 use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

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

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

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

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

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

Learn to streamline your machine learning workflows with tidymodels.

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

Learn how to pull character strings apart, put them back together and use the stringr package.

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

Ensure high data quality in data science and data engineering workflows with Pythons Great Expectations library.

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.

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

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

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.