Data, AI, and Cloud Courses

Learn the core techniques necessary to extract meaningful insights from time series data.

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

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

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

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

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

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

Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.

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

Learn how to approach and win competitions on Kaggle.

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

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

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

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

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

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 about the difference between batching and streaming, scaling streaming systems, and real-world applications.

Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.

In this course youll learn about basic experimental design, a crucial part of any data analysis.

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

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

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

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

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.