Data, AI, and Cloud Courses

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Learn to use the Bioconductor package limma for differential gene expression analysis.

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

Learn the fundamentals of valuing stocks.

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Enhance your Tableau skills with this case study on inventory analysis. Analyze a dataset, create calculated fields, and create visualizations.

Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!

Create multi-modal systems using OpenAIs text and audio models, including an end-to-end customer support chatbot!

In this course youll learn how to use data science for several common marketing tasks.

In this course youll learn how to apply machine learning in the HR domain.

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Learn Excel data validation to improve accuracy, create drop-downs, and manage inventory and orders with confidence.

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.

Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

Learn to analyze and model customer choice data in R.

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.