Data, AI, and Cloud Courses

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

In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.

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

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

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

Learn to create your own Python packages to make your code easier to use and share with others.

Learn to perform linear and logistic regression with multiple explanatory variables.

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.

Boost your coding with AI—guide your coding assistant to write, test, and document code effectively.

Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.

Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

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

Learn to perform linear and logistic regression with multiple explanatory variables.

Master sampling to get more accurate statistics with less data.

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

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

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

Learn how to work with Claude using the Anthropic API to solve real-world tasks and build AI-powered applications.

Learn to start developing deep learning models with Keras.

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

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

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

Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

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

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

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

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

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

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

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