Data, AI, and Cloud Courses

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

Learn how to design Power BI visualizations and reports with users in mind.

Master sampling to get more accurate statistics with less data.

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

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

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

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

Learn how to clean data with Apache Spark in Python.

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

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.

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

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

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

Explore AI and data monetization strategies, build ethical infrastructures, and align products with business goals.

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

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

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

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.

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

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

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

Learn about ARIMA models in Python and become an expert in time series analysis.

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

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

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

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

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

Master the key concepts of data management, from life cycle stages to security and governance.