Data, AI, and Cloud Courses

Learn to start developing deep learning models with Keras.

Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

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

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Create new features to improve the performance of your Machine Learning models.

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Learn about Large Language Models (LLMs) and how they are reshaping the business world.

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

Learn how to clean data with Apache Spark in Python.

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

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

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.

Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.

Learn how to blend business, data, and AI, and set goals to drive success with an effectively scalable AI Strategy.

Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

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

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

Master AWS security, governance, and cost optimization to prepare for the Cloud Practitioner certification.

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

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

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

Learn the fundamentals of data visualization using Google Sheets.

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

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Create interactive data visualizations in Python using Plotly.