Data, AI, and Cloud Courses

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

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

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

Learn how to clean data with Apache Spark in Python.

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Discover how Marketing Analysts use data to understand customers and drive business growth.

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Explore Azure services like Compute, Storage, and Automation, with hands-on experience.

Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

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

Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Build the foundation you need to think statistically and to speak the language of your data.

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Discover how the Pinecone vector database is revolutionizing AI application development!

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

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